Joint Model

We present several statistical models of syntactic constituent order for sentence realization. We compare several models, including simple joint models inspired by existing statistical parsing models, and several novel conditional …...

We present a semantic role labeling sys- tem submitted to the closed track of the CoNLL-2005 shared task. The system, in- troduced in (Toutanova et al., 2005), im- plements a …...

Despite much recent progress on accu- rate semantic role labeling, previous work has largely used independent classifiers, possibly combined with separate label se- quence models via Viterbi decoding. This stands …...

For many language technology applications, such as question answering, the overall sys- tem runs several independent processors over the data (such as a named entity recognizer, a coreference system, and …...

The character-based tagging approach is a dominant technique for Chinese word segmentation, and both discrimi- native and generative models can be adopted in that framework. However, generative and discriminative charac- …...

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 …...

Most previous studies of morphological dis- ambiguation and dependency parsing have been pursued independently. Morphological taggers operate on n-grams and do not take into account syntactic relations; parsers use the …...

We learn a joint model of sentence extraction and compression for multi-document summa- rization. Our model scores candidate sum- maries according to a combined linear model whose features factor over …...

Currently, Chinese event extraction systems suffer much from the low quality of annotated event corpora and the high ratio of pseudo trigger mentions to true ones. To resolve these two …...

Previous joint models of Chinese part-of-speech (POS) tagging and dependency parsing are extended from either graph- or transition-based dependency models. Our analysis shows that the two models have different error …...

Concept-to-text generation refers to the task of automatically producing textual output from non-linguistic input. We present a joint model that captures content selection (“what to say”) and surface realization (“how …...

We propose a joint model for unsuper- vised induction of sentiment, aspect and discourse information and show that by in- corporating a notion of latent discourse re- lations in the …...

Word-final /t/-deletion refers to a common phenomenon in spoken English where words such as /wEst/ “west” are pro- nounced as [wEs] “wes” in certain con- texts. Phonological variation like this …...

This paper introduces a graph-based semi- supervised joint model of Chinese word segmentation and part-of-speech tagging. The proposed approach is based on a graph-based label propagation technique. One constructs a …...

This paper proposes a nonparametric Bayesian method for inducing Part-of- Speech (POS) tags in dependency trees to improve the performance of statistical machine translation (SMT). In particular, we extend the …...

This paper presents G-FLOW, a novel system for coherent extractive multi-document sum- marization (MDS).1 Where previous work on MDS considered sentence selection and or- dering separately, G-FLOW introduces a joint …...

AbstractThe context in which language is used provides a strong signal for learning to recover its meaning. In this paper, we show it can be used within a grounded CCG …...

AbstractWe present a joint model of three core tasks in the entity analysis stack: coreference resolution (within-document clustering), named entity recognition (coarse semantic typing), and entity linking (matching to Wikipedia …...

We address the problem of automatically attributing quotations to speakers, which has great relevance in text mining and me- dia monitoring applications. While cur- rent systems report high accuracies for …...

In this paper, we propose a joint model for unsupervised Chinese word segmentation (CWS). Inspired by the “products of ex- perts” idea, our joint model firstly com- bines two generative …...

Microblogs have recently received widespread interest from NLP re- searchers. However, current tools for Japanese word segmentation and POS tagging still perform poorly on microblog texts. We developed an annotated …...

In this paper, we propose a new frame- work that unifies the output of three infor- mation extraction (IE) tasks - entity men- tions, relations and events as an informa- …...

AbstractSpace-delimited words in Turkish and Hebrew text can be further segmented into meaningful units, but syntactic and semantic context is necessary to predict segmentation. At the same time, predicting correct …...

Events and their coreference offer use- ful semantic and discourse resources. We show that the semantic and dis- course aspects of events interact with each other. However, traditional approaches ad- …...

We present a joint model for predicate argu- ment alignment. We leverage multiple sources of semantic information, including temporal ordering constraints between events. These are combined in a max-margin framework …...

This paper describes a joint model of word segmentation and phonological alternations, which takes unsegmented utterances as input and infers word segmentations and underlying phonological representations. The model is a …...

In a complex sentence comprised of one or more subclauses, the overt or hidden atti- tudes between the various entities depend on the factuality projection of the verbs, their polar …...

We cast sentence boundary detection and syntactic parsing as a joint problem, so an entire text document forms a training instance for transition-based dependency parsing. When trained with an early …...

AbstractUnderstanding stories – sequences of events – is a crucial yet challenging natural language understanding task. These events typically carry multiple aspects of semantics including actions, entities and emotions. Not …...

AbstractIn order to determine argument structure in text, one must understand how individual components of the overall argument are linked. This work presents the first neural network-based approach to link …...

Election manifestos document the inten- tions, motives, and views of political par- ties. They are often used for analysing party policies and positions on various is- sues, as well as …...

AbstractA spoken language understanding (SLU) system includes two main tasks, slot filling (SF) and intent detection (ID). The joint model for the two tasks is becoming a tendency in SLU. …...

AbstractOpen-domain targeted sentiment analysis aims to detect opinion targets along with their sentiment polarities from a sentence. Prior work typically formulates this task as a sequence tagging problem. However, such …...

AbstractThough deep learning has achieved significant success in various NLP tasks, most deep learning models lack the capability of encoding explicit domain knowledge to model complex causal relationships among different …...

AbstractExploiting sentence-level labels, which are easy to obtain, is one of the plausible methods to improve low-resource named entity recognition (NER), where token-level labels are costly to annotate. Current models …...

AbstractThe rise of online communication platforms has been accompanied by some undesirable effects, such as the proliferation of aggressive and abusive behaviour online. Aiming to tackle this problem, the natural …...

AbstractAspect-based sentiment analysis includes opinion aspect extraction and aspect sentiment classification. Researchers have attempted to discover the relationship between these two sub-tasks and have proposed the joint model for solving …...

AbstractBoth syntactic and semantic structures are key linguistic contextual clues, in which parsing the latter has been well shown beneficial from parsing the former. However, few works ever made an …...

AbstractAspect Sentiment Triplet Extraction (ASTE) is the task of extracting the triplets of target entities, their associated sentiment, and opinion spans explaining the reason for the sentiment. Existing research efforts …...

AbstractDefinition Extraction is the task to automatically extract terms and their definitions from text. In recent years, it attracts wide interest from NLP researchers. This paper describes the unixlong team’s …...

AbstractEnd-to-end relation extraction aims to identify named entities and extract relations between them. Most recent work models these two subtasks jointly, either by casting them in one structured prediction framework, …...

Journalists usually organize and present the contents of a news article following a well- defined structure. In this paper, we propose a novel joint model for structure-based news genre classification …...

AbstractWe present a joint model for entity-level relation extraction from documents. In contrast to other approaches - which focus on local intra-sentence mention pairs and thus require annotations on mention …...

AbstractSentiment analysis has attracted increasing attention in e-commerce. The sentiment polarities underlying user reviews are of great value for business intelligence. Aspect category sentiment analysis (ACSA) and review rating prediction …...

AbstractMulti-intent SLU can handle multiple intents in an utterance, which has attracted increasing attention. However, the state-of-the-art joint models heavily rely on autoregressive approaches, resulting in two issues: slow inference …...

AbstractWhile numerous attempts have been made to jointly parse syntax and semantics, high performance in one domain typically comes at the price of performance in the other. This trade-off contradicts …...

AbstractMulti-intent detection and slot filling joint model attracts more and more attention since it can handle multi-intent utterances, which is closer to complex real-world scenarios. Most existing joint models rely …...

AbstractIn conversational question answering (CQA), the task of question rewriting (QR) in context aims to rewrite a context-dependent question into an equivalent self-contained question that gives the same answer. In …...

AbstractImages are often more significant than only the pixels to human eyes, as we can infer, associate, and reason with contextual information from other sources to establish a more complete …...