F1 Measure

In this paper, we propose a semantic role label- ing method using a maximum entropy model, which enables not only to exploit rich features but also to alleviate the data …...

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 …...

. We build a class-based selection preference sub-model to in- corporate external semantic knowledge from two Chinese electronic se- mantic dictionaries. This sub-model is combined with modifier-head gen- eration sub-model. …...

. The current state of Philippine linguistic resources, which includes formal grammars, electronic dictionaries and corpora are not yet significant to address industrial- strength language technologies. This paper discusses a …...

Parse-tree paths are commonly used to incor- porate information from syntactic parses into NLP systems. These systems typically treat the paths as atomic (or nearly atomic) features; these features are …...

Keyphrases are widely used as a brief summary of documents. Since man- ual assignment is time-consuming, vari- ous unsupervised ranking methods based on importance scores are proposed for keyphrase extraction. …...

In the application of Conditional Random Fields (CRF), a huge number of features is typically taken into ac- count. These models can deal with inter-dependent and correlated data with an …...

Semantic Role Labeling (SRL) has proved to be a valuable tool for performing auto- matic analysis of natural language texts. Currently however, most systems rely on a large training set, …...

This paper explores the influence of text pre- processing techniques on plagiarism detection. We examine stop-word removal, lemmatization, number replacement, synonymy recognition, and word generalization. We also look into the …...

Comparing one thing with another is a typical part of human decision making process. How- ever, it is not always easy to know what to compare and what are the …...

AbstractAn increasing demand for new language resources of recent EU members and accessing countries has in turn initiated the development of different language tools and resources, such as alignment tools …...

This paper proposes a novel feature for conditional random field (CRF) model in Chinese word segmentation system. The system uses a conditional random field as machine learning model with one …...

Mining of transliterations from comparable or parallel text can enhance natural language processing applications such as machine translation and cross language information retrieval. This paper presents an enhanced transliteration mining …...

We present the results we obtain using our RegMT system, which uses transductive re- gression techniques to learn mappings be- tween source and target features of given par- allel corpora …...

This work represents several unsupervised feature selections based on frequent strings that help improve conditional random fields (CRF) model for Chinese word segmentation (CWS). These features include character-based N-gram (CNG), …...

We present a novel adaptive clustering model for coreference resolution in which the expert rules of a state of the art deterministic sys- tem are used as features over pairs …...

AbstractAutomatic annotation of temporal expressions is a research challenge of great interest in the field of information extraction. Gold standard temporally-annotated resources are limited in size, which makes research using …...

We consider the problem of inducing grapheme-to-phoneme mappings for un- known languages written in a Latin alphabet. First, we collect a data-set of 107 languages with known grapheme-phoneme relationships, along …...

Drug name entity recognition focuses on identifying concepts appearing in the text that correspond to a chemical substance used in pharmacology for treatment, cure, prevention or diagnosis of diseases. This …...

. In event-based Information Extraction systems, a major task is the filling from a text of a template gathering information related to a particular event. Such template filling may be …...

Most of the recent literature on Sentiment Analysis over Twitter is tied to the idea that the senti- ment is a function of an incoming tweet. However, tweets are filtered …...

AbstractThis paper investigates the discursive phenomenon called other-repetitions (OR), particularly in the context of spontaneous French dialogues. It focuses on their automatic detection and characterization. A method is proposed to …...

This paper describes LIMSI participation to the WMT’14 Shared Task on Qual- ity Estimation; we took part to the word- level quality estimation task for English to Spanish translations. Our …...

This paper proposed a method that can automatically detect syntax errors in Chinese sentences. The algorithm for identifying syntax errors proposed in this study is known as KNGED, which uses …...

Target entity disambiguation (TED), the task of identifying target entities of the same domain, has been recognized as a critical step in various important applica- tions. In this paper, we …...

In this shared task, we present evaluations on two related tasks Paraphrase Identification (PI) and Semantic Textual Similarity (SS) sys- tems for the Twitter data. Given a pair of sentences, …...

Suicide is one of major public health problems worldwide. Traditionally, suicidal ideation is assessed by surveys or interviews, which lacks of a real-time assessment of personal men- tal state. Online …...

AbstractArgument labeling of explicit discourse relations is a challenging task. The state of the art systems achieve slightly above 55% F-measure but require hand-crafted features. In this paper, we propose …...

AbstractRelation Extraction (RE) consists in detecting and classifying semantic relations between entities in a sentence. The vast majority of the state-of-the-art RE systems relies on morphosyntactic features and supervised machine …...

AbstractContextual embeddings are proved to be overwhelmingly effective to the task of Word Sense Disambiguation (WSD) compared with other sense representation techniques. However, these embeddings fail to embed sense knowledge …...

AbstractOne of the remaining challenges for aspect term extraction in sentiment analysis resides in the extraction of phrase-level aspect terms, which is non-trivial to determine the boundaries of such terms. …...

In this paper, we propose a method of ex- tracting novel character information such as characters’ names, gender, age, occupations, and a part of relationships between characters from synopses of …...

AbstractThis paper describes the BERT-based models proposed for two subtasks in SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles. We first build the model for Span Identification (SI) …...

AbstractIn this study, we created an imperative corpus with speech conversations from dialogues in The Big Bang Theory and with the written comments in Wikipedia’s Articles for Deletion discussions. For …...

AbstractThis paper tackles a new task for event entity recognition (EER). Different from named entity recognizing (NER) task it only identifies the named entities which are related to a specific …...

AbstractStereotypical character roles-also known as archetypes or dramatis personae-play an important function in narratives: they facilitate efficient communication with bundles of default characteristics and associations and ease understanding of those …...

AbstractStandard automatic metrics, e.g. BLEU, are not reliable for document-level MT evaluation. They can neither distinguish document-level improvements in translation quality from sentence-level ones, nor identify the discourse phenomena that …...

AbstractThe task of Chinese Spelling Check (CSC) is aiming to detect and correct spelling errors that can be found in the text. While manually annotating a high-quality dataset is expensive …...