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The dialogue strategies used by a spoken dialogue system strongly influence performance and user sat- isfaction. An ideal system would not use a single fixed strategy, but would adapt to …...

We are developing corpus-based techniques for iden- tifying semantic relations at an intermediate level of description (more specific than those used in case frames, but more general than those used …...

We present a framework for statistical machine translation of natural languages based on direct maximum entropy mod- els, which contains the widely used sour- ce-channel approach as a special case. …...

Coreferential information of a candidate, such as the properties of its antecedents, is important for pronoun resolution because it reflects the salience of the candidate in the local discourse. Such …...

Probabilistic models have been effective in re- solving prepositional phrase attachment am- biguity, but sparse data remains a significant problem. We propose a solution based on similarity-based smoothing, where the …...

Existing named entity (NE) transliteration approaches often exploit a general model to transliterate NEs, regardless of their origins. As a result, both a Chinese name and a French name (assuming …...

German has a productive morphology and allows the creation of complex words which are often highly ambiguous. This paper reports on the development of a head-lexicalized PCFG for the disam- …...

Statistical machine translation relies heavily on the available training data. In some cases it is necessary to limit the amount of training data that can be created for or actually …...

Humor is one of the most interesting and puzzling aspects of human behavior. De- spite the attention it has received in fields such as philosophy, linguistics, and psy- chology, there …...

Recent years have seen increasing re- search on extracting and using temporal information in natural language applica- tions. However most of the works found in the literature have focused on …...

The majority of the state-of-the-art ap- proaches to recognizing textual entailment focus on defining a generic approach to RTE. A generic approach never works well for every single entailment pair: …...

This paper introduces a novel evaluation framework for question series and em- ploys it to explore the effectiveness of QA and IR systems at addressing users’ infor- mation needs. The …...

In this paper we are reporting the re- sults obtained participating in the “Eval- uating Word Sense Induction and Dis- crimination Systems” task of Semeval 2007. Our totally unsupervised system …...

Inclusions from other languages can be a significant source of errors for monolin- gual parsers. We show this for English in- clusions, which are sufficiently frequent to present a problem …...

This paper presents a translation model that is based on tree sequence alignment, where a tree sequence refers to a single sequence of sub- trees that covers a phrase. The …...

Event reference identification is often treated as a sentence level classification task. However, several different event ref- erences can occur within a single sentence. We present a set of experiments …...

Traditionally, statistical machine translation systems have relied on parallel bi-lingual data to train a translation model. While bi-lingual parallel data are expensive to generate, mono- lingual data are relatively common. …...

We examine the problem of content selection in statistical novel sentence generation. Our approach models the processes performed by professional editors when incorporating ma- terial from additional sentences to support …...

This paper presents a first-order logic learn- ing approach to determine rhetorical relations between discourse segments. Beyond lin- guistic cues and lexical information, our ap- proach exploits compositional semantics and …...

Automatically extracting social meaning and intention from spoken dialogue is an impor- tant task for dialogue systems and social com- puting. We describe a system for detecting elements of interactional …...

Experiments are reported that investi- gate the effect of various source docu- ment representations on the accuracy of the sentence extraction phase of a multi- document summarisation task. A novel …...

We present an implicit discourse relation classifier in the Penn Discourse Treebank (PDTB). Our classifier considers the con- text of the two arguments, word pair infor- mation, as well as …...

We describe a pattern-based system for polarity classification from texts. Our system is currently restricted to the positive, negative or neutral po- larity of phrases and sentences. It analyses the …...

We define a probabilistic morphological ana- lyzer using a data-driven approach for Syriac in order to facilitate the creation of an annotated corpus. Syriac is an under-resourced Semitic language for …...

Prompt and knowledgeable responses to cus- tomers’ emails are critical in maximizing cus- tomer satisfaction. Such emails often con- tain complaints about unfair treatment due to negligence, incompetence, rigid protocols, …...

We report on work in progress on extract- ing lexical simplifications (e.g., “collaborate” → “work together”), focusing on utilizing edit histories in Simple English Wikipedia for this task. We consider …...

This paper presents a supervised approach for identifying generic noun phrases in context. Generic statements express rule- like knowledge about kinds or events. Therefore, their identification is important for the …...

This paper improves the use of pseudo- words as an evaluation framework for selectional preferences. While pseudo- words originally evaluated word sense disambiguation, they are now commonly used to evaluate …...

In this paper we present a chunk based keyphrase extraction method for scientific articles. Different from most previous sys- tems, supervised machine learning algo- rithms are not used in our …...

In this paper we develop an approach to tackle the problem of verb selection for learners of English as a second language (ESL) by using features from the output of …...

Polysemy is a major characteristic of natu- ral languages. Like words, syntactic forms can have several meanings. Understanding the correct meaning of a syntactic form is of great importance to …...

Datasets annotated with semantic roles are an important prerequisite to developing high- performance role labeling systems. Unfortu- nately, the reliance on manual annotations, which are both difficult and highly expen- …...

In citation-based summarization, text written by several researchers is leveraged to identify the important aspects of a target paper. Previ- ous work on this problem focused almost ex- clusively on …...

We present a novel method for record extrac- tion from social streams such as Twitter. Un- like typical extraction setups, these environ- ments are characterized by short, one sentence messages …...

Information published in online stock invest- ment message boards, and more recently in stock microblogs, is considered highly valu- able by many investors. Previous work fo- cused on aggregation of …...

Part-of-speech language modeling is com- monly used as a component in statistical ma- chine translation systems, but there is mixed evidence that its usage leads to significant im- provements. We …...

AbstractIn this paper, we investigate the usage of a non-canonical German passive alternation for ditransitive verbs, the recipient passive, in naturally occuring corpus data. We propose a classifier that predicts …...

In this paper, we define a new type of summary for sentiment analysis: a single- sentence summary that consists of a sup- porting sentence that conveys the overall sentiment of …...

Current Chinese event extraction systems suffer much from two problems in trigger identification: unknown triggers and word segmentation errors to known triggers. To resolve these problems, this paper proposes two …...

This paper implements and compares three different strategies to use English as pivot language for Chinese-Japanese patent translation: corpus enrichment, sentence pivot translation and phrase pivot translation. Our results show …...

Many works (of both fiction and non-fiction) span multiple, intersecting narratives, each of which constitutes a story in its own right. In this work I introduce the task of multiple …...

The UOW submissions to the Semantic Tex- tual Similarity task at SemEval-2012 use a supervised machine learning algorithm along with features based on lexical, syntactic and semantic similarity metrics to …...

The performance of NLP classifiers largely depends on the quality of the features considered for prediction (feature engineering). However, as the number of features increases, the more likely overfit- ting …...

Until recently, the application of discrimina- tive training to log linear-based statistical ma- chine translation has been limited to tuning the weights of a limited number of features or training …...

This paper aims at effective use of training da- ta by extracting sentences from large general- domain corpora to adapt statistical machine translation systems to domain-specific data. We regard this …...

Most NLP tools are applied to text that is dif- ferent from the kind of text they were eval- uated on. Common evaluation practice pre- scribes significance testing across data …...

We introduce the novel task of automati- cally generating questions that are relevant to a text but do not appear in it. One mo- tivating example of its application is …...

This paper proposes a novel approach that uti- lizes a machine learning method to improve pivot-based statistical machine translation (SMT). For language pairs with few bilingual data, a possible solution …...

Non-expert annotation services like Amazon’s Mechanical Turk (AMT) are cheap and fast ways to evaluate systems and provide categor- ical annotations for training data. Unfortu- nately, some annotators choose bad …...

We address the problem of informal word recognition in Chinese microblogs. A key problem is the lack of word delimiters in Chinese. We exploit this reliance as an opportunity: recognizing …...

In this paper, we describe SemEval-2013 Task 4: the definition, the data, the evaluation and the results. The task is to capture some of the meaning of English noun compounds …...

Finding concepts in natural language ut- terances is a challenging task, especially given the scarcity of labeled data for learn- ing semantic ambiguity. Furthermore, data mismatch issues, which arise when …...

The popularity of the user generated content, such as Twitter, has made it a rich source for the sentiment analysis and opinion min- ing tasks. This paper presents our study …...

The article describes our system submitted to the SemEval-2014 task on Aspect-Based Sentiment Analy- sis. The methods based on distribut- ed representations of words for the aspect term extraction and …...

Clustering aspect-related phrases in terms of product’s property is a precursor pro- cess to aspect-level sentiment analysis which is a central task in sentiment analy- sis. Most of existing methods …...

We outline the first application of Native Language Identification (NLI) to Finnish learner data. NLI is the task of predicting an author’s first language using writings in an acquired language. …...

AbstractAnnotation of data is a time-consuming process, but necessary for many state-of-the-art solutions to NLP tasks, including semantic role labeling (SRL). In this paper, we show that language models may …...

Languages spoken by immigrants change due to contact with the local languages. Capturing these changes is problematic for current language technologies, which are typically developed for speakers of the standard …...

Previous studies have shown that health reports in social media, such as Dai- lyStrength and Twitter, have potential for monitoring health conditions (e.g. adverse drug reactions, infectious diseases) in par- …...

Word segmentation is helpful in Chinese nat- ural language processing in many aspects. However it is showed that different word seg- mentation strategies do not affect the per- formance of …...

Vector-space models derived from corpora are an effective way to learn a representa- tion of word meaning directly from data, and these models have many uses in prac- tical applications. …...

This paper demonstrates the effectiveness of a Long Short-Term Memory language model in our initial efforts to generate un- constrained rap lyrics. The goal of this model is to generate …...

Most of previous work in knowledge base (KB) completion has focused on the problem of relation extraction. In this work, we focus on the task of inferring missing entity type …...

This paper presents an overview of the 6th ALTA shared task that ran in 2015. The task was to identify in English texts all the potential cognates from the per- …...

In this paper we describe a semi-automated approach to extend morphological lexicons by defining the prediction of the correct inflectional paradigm and the lemma for an unknown word as a …...

We propose a summarization approach for scientific articles which takes advantage of citation-context and the document discourse model. While citations have been previously used in generating scientific summaries, they lack …...

We present an LSTM approach to deletion-based sentence compression where the task is to translate a sentence into a sequence of zeros and ones, cor- responding to token deletion decisions. …...

This paper reports on our participation in SemEval-2015 Task 12, which was devoted to Aspect-Based Sentiment Analysis. Partic- ipants were required to identify the category (entity and attribute), the opinion …...

AbstractExisting work on domain adaptation for statistical machine translation has consistently assumed access to a small sample from the test distribution (target domain) at training time. In practice, however, the …...

The automatic detection of causal relation- ships in text is important for natural lan- guage understanding. This task has proven to be difficult, however, due to the need for world …...

As a new generation of cognitive robots start to enter our lives, it is important to enable robots to follow human commands and to learn new actions from human lan- …...

Events and entities are closely related; entities are often actors or participants in events and events without entities are uncommon. The interpretation of events and entities is highly contextually dependent. …...

AbstractChinese sentences are written as sequences of characters, which are elementary units of syntax and semantics. Characters are highly polysemous in forming words. We present a position-sensitive skip-gram model to …...

AbstractThis paper presents NileULex, which is an Arabic sentiment lexicon containing close to six thousands Arabic words and compound phrases. Forty five percent of the terms and expressions in the …...

Intelligent assistants on mobile devices, such as Siri, have recently gained con- siderable attention as novel applications of dialogue technologies. A tremendous amount of real users of intelligent assis- tants …...

AbstractCross document event coreference (CDEC) is an important task that aims at aggregating event-related information across multiple documents. We revisit the evaluation for CDEC, and discover that past works have …...

Manually constructed taxonomies provide a crucial resource for many NLP technologies, yet these resources are often limited in their lexical coverage due to their construction pro- cedure. While multiple approaches …...

This paper presents a solution to Semeval 2016 Task 14 which asks for a system that is able to insert new lemmas into WordNet. Our system aims to do this …...

AbstractCollecting spontaneous speech corpora that are open-ended, yet topically constrained, is increasingly popular for research in spoken dialogue systems and speaker state, inter alia. Typically, these corpora are labeled by …...

AbstractWe examine the effects of particular orderings of sentence pairs on the on-line training of neural machine translation (NMT). We focus on two types of such orderings: (1) ensuring that …...

AbstractIn the wake of a polarizing election, the cyber world is laden with hate speech. Context accompanying a hate speech text is useful for identifying hate speech, which however has …...

Machine translation quality estimation is a challenging task in the WMT evaluation campaign. Feature extrac- tion plays an important role in auto- matic quality estimation, and in this paper, we …...

AbstractIn this paper, we introduce a new distributional method for modeling predicate-argument thematic fit judgments. We use a syntax-based DSM to build a prototypical representation of verb-specific roles: for every …...

Automatic post-editing (APE) is a challenging task on WMT evaluation campaign. We find that only a small number of edit operations are required for most machine translation outputs, through analysis …...

AbstractThis work describes the Neural Machine Translation (NMT) system of the RWTH Aachen University developed for the English$German tracks of the evaluation campaign of the International Workshop on Spoken Language …...

Acquiring information on incidents and acci- dents from social media can be useful for broadcasters to report news faster. However, many tweets including words related to inci- dents and accidents …...

AbstractThis paper discusses on task 1, “Affect in Tweets” sharedtask, conducted in SemEval-2018. This task comprises of various subtasks, which required participants to analyse over different emotions and sentiments based …...

Natural language interfaces to databases systems allow the user to use natural language to interrogate a database. Current systems mainly focus on simple queries but neglect nested queries, which are …...

AbstractWe propose a Long Short Term Memory Neural Network model for irony detection in tweets in this paper. Our model is trained using word embeddings and emoji embeddings. We show …...

AbstractTransfer learning has been proven as an effective technique for neural machine translation under low-resource conditions. Existing methods require a common target language, language relatedness, or specific training tricks and …...

Phrase-based machine translation provides the system developer with controls that enable fine-grained control over machine translation output. One approach to provide similar control in neural machine transla- tion is placeholding …...

AbstractDifferent news articles about the same topic often offer a variety of perspectives: an article written about gun violence might emphasize gun control, while another might promote 2nd Amendment rights, …...

AbstractPrevious research shows that eye-tracking data contains information about the lexical and syntactic properties of text, which can be used to improve natural language processing models. In this work, we …...

AbstractEfficiently building an adversarial attacker for natural language processing (NLP) tasks is a real challenge. Firstly, as the sentence space is discrete, it is difficult to make small perturbations along …...

AbstractRecent advancements in Internet and Mobile infrastructure have resulted in the development of faster and efficient platforms of communication. These platforms include speech, facial and text-based conversational mediums. Majority of …...

AbstractIn this paper, we present our contribution to SemEval 2019 Task 5 Multilingual Detection of Hate, specifically in the Subtask A (English and Spanish). We compare different configurations of shallow …...

AbstractMetonymy is a figure of speech in which an entity is referred to by another related entity. The existing datasets of metonymy are either too small in size or lack …...

AbstractTraining a supervised neural network classifier typically requires many annotated training samples. Collecting and annotating a large number of data points are costly and sometimes even infeasible. Traditional annotation process …...

AbstractIn this paper, we propose a new task of machine translation (MT), which is based on no parallel sentences but can refer to a ground-truth bilingual dictionary. Motivated by the …...

AbstractWe developed an extensible, comprehensive Wiktionary parser that improves over several existing parsers. We predict the etymology of a word across the full range of etymology types and languages in …...

AbstractWe introduce CGA, a conditional VAE architecture, to control, generate, and augment text. CGA is able to generate natural English sentences controlling multiple semantic and syntactic attributes by combining adversarial …...

AbstractBiomedical event extraction is a crucial task in order to automatically extract information from the increasingly growing body of biomedical literature. Despite advances in the methods in recent years, most …...

AbstractWe propose a novel approach to cross-lingual dependency parsing based on word reordering. The words in each sentence of a source language corpus are rearranged to meet the word order …...

AbstractThe current aspect extraction methods suffer from boundary errors. In general, these errors lead to a relatively minor difference between the extracted aspects and the ground-truth. However, they hurt the …...

AbstractArtificial General Intelligence (AGI) is showing growing performance in numerous applications - beating human performance in Chess and Go, using knowledge bases and text sources to answer questions (SQuAD) and …...

AbstractThis paper introduces our systems for the first two subtasks of SemEval Task4: Commonsense Validation and Explanation. To clarify the intention for judgment and inject contrastive information for selection, we …...

AbstractEvent Detection (ED) is a fundamental task in automatically structuring texts. Due to the small scale of training data, previous methods perform poorly on unseen/sparsely labeled trigger words and are …...

AbstractMulti-hop Question Generation (QG) aims to generate answer-related questions by aggregating and reasoning over multiple scattered evidence from different paragraphs. It is a more challenging yet under-explored task compared to …...

AbstractIn this paper, we demonstrate our machine translation system applied for the Chinese-Japanese bidirectional translation task (aka. open domain translation task) for the IWSLT 2020. Our model is based on …...

AbstractIt is appealing to have a system that generates a story or scripts automatically from a storyline, even though this is still out of our reach. In dialogue systems, it …...

AbstractSpelling error correction is an important yet challenging task because a satisfactory solution of it essentially needs human-level language understanding ability. Without loss of generality we consider Chinese spelling error …...

AbstractVerifying fact on semi-structured evidence like tables requires the ability to encode structural information and perform symbolic reasoning. Pre-trained language models trained on natural language could not be directly applied …...

AbstractGiven a video with aligned dialogue, people can often infer what is more likely to happen next. Making such predictions requires not only a deep understanding of the rich dynamics …...

AbstractWe propose the novel Within-Between Relation model for recognizing lexical-semantic relations between words. Our model integrates relational and distributional signals, forming an effective sub-space representation for each relation. We show …...

AbstractZero pronoun recovery and resolution aim at recovering the dropped pronoun and pointing out its anaphoric mentions, respectively. We propose to better explore their interaction by solving both tasks together, …...

AbstractUser stance detection entails ascertaining the position of a user towards a target, such as an entity, topic, or claim. Recent work that employs unsupervised classification has shown that performing …...

AbstractModern classification models tend to struggle when the amount of annotated data is scarce. To overcome this issue, several neural few-shot classification models have emerged, yielding significant progress over time, …...

Recently, several studies have proposed pre- trained encoder-decoder models using mono- lingual data, such as BART, which can im- prove the accuracy of seq2seq tasks via fine- tuning with task-specific …...

AbstractCurrent commonsense reasoning research focuses on developing models that use commonsense knowledge to answer multiple-choice questions. However, systems designed to answer multiple-choice questions may not be useful in applications that …...

AbstractMultilingual neural machine translation (MNMT) learns to translate multiple language pairs with a single model, potentially improving both the accuracy and the memory-efficiency of deployed models. However, the heavy data …...

AbstractWith counterfactual bandit learning, models can be trained based on positive and negative feedback received for historical predictions, with no labeled data needed. Such feedback is often available in real-world …...

AbstractThe detection of hyperbole is an important stepping stone to understanding the intentions of a hyperbolic utterance. We propose a model that combines pre-trained language models with privileged information for …...

AbstractWe consider the problem of multi-label classification, where the labels lie on a hierarchy. However, unlike most existing works in hierarchical multi-label classification, we do not assume that the label-hierarchy …...

AbstractSemEval-2021 Task 8: MeasEval aims at improving the machine understanding of measurements in scientific texts through a set of entity and semantic relation extraction sub-tasks on identifying quantity spans along …...

AbstractIn entity linking, mentions of named entities in raw text are disambiguated against a knowledge base (KB). This work focuses on linking to unseen KBs that do not have training …...

AbstractOnline reviews are an essential aspect of online shopping for both customers and retailers. However, many reviews found on the Internet lack in quality, informativeness or helpfulness. In many cases, …...

Sensor names as alphanumeric strings typi- cally encode their key contextual information such as their function or physical location. We focus here on sensors used in smart build- ing applications. …...

AbstractMost current neural machine translation models adopt a monotonic decoding order of either left-to-right or right-to-left. In this work, we propose a novel method that breaks up the limitation of …...

AbstractNatural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), has been one of the central tasks in Artificial Intelligence (AI) and Natural Language Processing (NLP). RTE between the …...

AbstractWomen are frequently targeted online with hate speech and misogyny using tweets, memes, and other forms of communication. This paper describes our system for Task 5 of SemEval-2022: Multimedia Automatic …...

Integrating translation memories (TM) into neural machine translation (NMT) has been shown to improve translation quality. We test various schemes to integrate translation sug- gestions into an NMT system without …...

AbstractUnderstanding narrative flow and text coherence in long-form documents (novels) remains an open problem in NLP.To gain insight, we explore the task of chapter ordering, reconstructing the original order of …...

AbstractProducing a reduced version of a source text, as in generic or focused summarization, inherently involves two distinct subtasks: deciding on targeted content and generating a coherent text conveying it. …...

AbstractMultiword expressions (MWEs) or idiomaticity are common phenomenon in natural languages. Current pre-trained language models cannot effectively capture the meaning of these MWEs. The reason is that two normal words, …...

AbstractThe speaker-follower models have proven to be effective in vision-and-language navigation, where a speaker model is used to synthesize new instructions to augment the training data for a follower navigation …...

AbstractGender discrimination is a serious and widespread problem on social media and online in general. Besides offensive messages, memes are one of the main means of dissemination for such content. …...

AbstractIn this paper, we propose a mixture model-based end-to-end method to model the syntactic-semantic dependency correlation in Semantic Role Labeling (SRL). Semantic dependencies in SRL are modeled as a distribution …...

AbstractAnglicisms are a challenge in German speech recognition. Due to their irregular pronunciation compared to native German words, automatically generated pronunciation dictionaries often contain incorrect phoneme sequences for Anglicisms. In …...

AbstractThis paper describes anonymous submission to the WMT 2022 Quality Estimation shared task. We participate in Task 1: Quality Prediction for both sentence and word-level quality prediction tasks. Our system …...

AbstractRetriever-reader models achieve competitive performance across many different NLP tasks such as open question answering and dialogue conversations. In this work, we notice these models easily overfit the top-rank retrieval …...

AbstractThis paper describes submission to the WMT 2022 Quality Estimation shared task (Task 1: sentence-level quality prediction). We follow a simple and intuitive approach, which consists of estimating MT quality …...

AbstractIn this paper, we describe our efforts at SemEval 2022 Shared Task 4 on Patronizing and Condescending Language (PCL) Detection. This is the first shared task to detect PCL which …...

AbstractThe University of Edinburgh participated in the WMT22 shared task on code-mixed translation. This consists of two subtasks: i) generating code-mixed Hindi/English (Hinglish) text generation from parallel Hindi and English …...

AbstractRecent unsupervised topic modelling ap-proaches that use clustering techniques onword, token or document embeddings can ex-tract coherent topics. A common limitationof such approaches is that they reveal noth-ing about inter-topic …...

AbstractIn the context of the Multimedia Automatic Misogyny Identification (MAMI) competition 2022, we developed a framework for extracting lexical-semantic features from text and combine them with semantic descriptions of images, …...

AbstractSarcasm has gained notoriety for being difficult to detect by machine learning systems due to its figurative nature. In this paper, Bidirectional Encoder Representations from Transformers (BERT) model has been …...

AbstractProbing is popular to analyze whether linguistic information can be captured by a well-trained deep neural model, but it is hard to answer how the change of the encoded linguistic …...

AbstractIn this paper, we introduce ELECTRA-style tasks to cross-lingual language model pre-training. Specifically, we present two pre-training tasks, namely multilingual replaced token detection, and translation replaced token detection. Besides, we …...

AbstractSocial media is one of the most highly sought resources for analyzing characteristics of the language by its users. In particular, many researchers utilized various linguistic features of mental health …...

AbstractMemes can sway people’s opinions over social media as they combine visual and textual information in an easy-to-consume manner. Since memes instantly turn viral, it becomes crucial to infer their …...

AbstractWith multilingual machine translation (MMT) models continuing to grow in size and number of supported languages, it is natural to reuse and upgrade existing models to save computation as data …...

AbstractThis paper describes our participation as team FramingFreaks in the SemEval-2023 task 3 “Category and Framing Predictions in online news in a multi-lingual setup.” We participated in subtasks 1 and …...

AbstractIn this paper, we present the KU x Upstage team’s submission for the Special Task on Formality Control on Spoken Language Translation, which involves translating English into four languages with …...

AbstractWe present Reddit Health Online Talk (RedHOT), a corpus of 22,000 richly annotated social media posts from Reddit spanning 24 health conditions. Annotations include demarcations of spans corresponding to medical …...

AbstractWe demonstrate a simple yet effective approach to augmenting training data for multilingual named entity recognition using translations. The named entity spans from the original sentences are transferred to translations …...

AbstractWhen we interact with other humans, humanvalues guide us to consider the human element. As we shall see, value analysis in NLP hasbeen applied to personality profiling but not toargument …...

AbstractTo understand a legal document for real-world applications, SemEval-2023 Task 6 proposes a shared Subtask A, rhetorical roles (RRs) prediction, which requires a system to automatically assign a RR label …...