pwc-archive/papers-with-abstracts huggingface dataset:
A Study of the Bump Alternation in Japanese from the Perspective of Extended/Onset Causation
Authors: Natsuno Aoki, Kentaro Nakatani
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Object

This paper deals with a seldom studied object/oblique alternation phenomenon in Japanese, which. We call this the bump alternation. This phenomenon, first discussed by Sadanobu (1990), is similar to the English with/against alternation. For example, compare hit the wall with the bat [=immobile-as-direct-object frame] to hit the bat against the wall [=mobile-as-direct-object frame]). However, in the Japanese version, the case frame remains constant. Although we fundamentally question Sadanobu{'}s acceptability judgment, we also claim that the causation type (i.e., whether the event is an instance of onset or extended causation; Talmy, 1988; 2000) could make an improvement. An extended causative interpretation could improve the acceptability of the otherwise awkward immobile-as-direct-object frame. We examined this claim through a rating study, and the results showed an interaction between the Causation type (extended/onset) and the Object type (mobile/immobile) in the direction we predicted. We propose that a perspective shift on what is moving causes the {``}extended causation{''} advantage.
GhoSt-PV: A Representative Gold Standard of German Particle Verbs
Authors: Stefan Bott, Nana Khvtisavrishvili, Max Kisselew, Sabine Schulte im Walde
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12

German particle verbs represent a frequent type of multi-word-expression that forms a highly productive paradigm in the lexicon. Similarly to other multi-word expressions, particle verbs exhibit various levels of compositionality. One of the major obstacles for the study of compositionality is the lack of representative gold standards of human ratings. In order to address this bottleneck, this paper presents such a gold standard data set containing 400 randomly selected German particle verbs. It is balanced across several particle types and three frequency bands, and accomplished by human ratings on the degree of semantic compositionality.
Discovering Potential Terminological Relationships from Twitter's Timed Content
Authors: Mohammad Daoud, Daoud Daoud
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Dynamic Time Warping, Information Retrieval, Machine Translation

This paper presents a method to discover possible terminological relationships from tweets. We match the histories of terms (frequency patterns). Similar history indicates a possible relationship between terms. For example, if two terms (t1, t2) appeared frequently in Twitter at particular days, and there is a {`}similarity{'} in the frequencies over a period of time, then t1 and t2 can be related. Maintaining standard terminological repository with updated relationships can be difficult; especially in a dynamic domain such as social media where thousands of new terms (neology) are coined every day. So we propose to construct a raw repository of lexical units with unconfirmed relationships. We have experimented our method on time-sensitive Arabic terms used by the online Arabic community of Twitter. We draw relationships between these terms by matching their similar frequency patterns (timelines). We use dynamic time warping as a similarity measure. For evaluation, we have selected 630 possible terms (we call them preterms) and we matched the similarity of these terms over a period of 30 days. Around 270 correct relationships were discovered with a precision of 0.61. These relationships were extracted without considering the textual context of the term.
Lexfom: a lexical functions ontology model
Authors: Alexs Fonseca, ro, Fatiha Sadat, Fran{\c{c}}ois Lareau
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: model, Relation

A lexical function represents a type of relation that exists between lexical units (words or expressions) in any language. For example, the antonymy is a type of relation that is represented by the lexical function Anti: Anti(big) = small. Those relations include both paradigmatic relations, i.e. vertical relations, such as synonymy, antonymy and meronymy and syntagmatic relations, i.e. horizontal relations, such as objective qualification (legitimate demand), subjective qualification (fruitful analysis), positive evaluation (good review) and support verbs (pay a visit, subject to an interrogation). In this paper, we present the Lexical Functions Ontology Model (lexfom) to represent lexical functions and the relation among lexical units. Lexfom is divided in four modules: lexical function representation (lfrep), lexical function family (lffam), lexical function semantic perspective (lfsem) and lexical function relations (lfrel). Moreover, we show how it combines to Lexical Model for Ontologies (lemon), for the transformation of lexical networks into the semantic web formats. So far, we have implemented 100 simple and 500 complex lexical functions, and encoded about 8,000 syntagmatic and 46,000 paradigmatic relations, for the French language.
A Proposal for combining ``general'' and specialized frames
Authors: Marie-Claude L{'} Homme, Carlos Subirats, Beno{\^\i}t Robichaud
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12

The objectives of the work described in this paper are: 1. To list the differences between a general language resource (namely FrameNet) and a domain-specific resource; 2. To devise solutions to merge their contents in order to increase the coverage of the general resource. Both resources are based on Frame Semantics (Fillmore 1985; Fillmore and Baker 2010) and this raises specific challenges since the theoretical framework and the methodology derived from it provide for both a lexical description and a conceptual representation. We propose a series of strategies that handle both lexical and conceptual (frame) differences and implemented them in the specialized resource. We also show that most differences can be handled in a straightforward manner. However, some more domain specific differences (such as frames defined exclusively for the specialized domain or relations between these frames) are likely to be much more difficult to take into account since some are domain-specific.
Antonymy and Canonicity: Experimental and Distributional Evidence
Authors: Andreana Pastena, Aless Lenci, ro
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12

The present paper investigates the phenomenon of antonym canonicity by providing new behavioural and distributional evidence on Italian adjectives. Previous studies have showed that some pairs of antonyms are perceived to be better examples of opposition than others, and are so considered representative of the whole category (e.g., Deese, 1964; Murphy, 2003; Paradis et al., 2009). Our goal is to further investigate why such canonical pairs (Murphy, 2003) exist and how they come to be associated. In the literature, two different approaches have dealt with this issue. The lexical-categorical approach (Charles and Miller, 1989; Justeson and Katz, 1991) finds the cause of canonicity in the high co-occurrence frequency of the two adjectives. The cognitive-prototype approach (Paradis et al., 2009; Jones et al., 2012) instead claims that two adjectives form a canonical pair because they are aligned along a simple and salient dimension. Our empirical evidence, while supporting the latter view, shows that the paradigmatic distributional properties of adjectives can also contribute to explain the phenomenon of canonicity, providing a corpus-based correlate of the cognitive notion of salience.
Categorization of Semantic Roles for Dictionary Definitions
Authors: Vivian Silva, H, Siegfried schuh, Andr{\'e} Freitas
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Question Answering

Understanding the semantic relationships between terms is a fundamental task in natural language processing applications. While structured resources that can express those relationships in a formal way, such as ontologies, are still scarce, a large number of linguistic resources gathering dictionary definitions is becoming available, but understanding the semantic structure of natural language definitions is fundamental to make them useful in semantic interpretation tasks. Based on an analysis of a subset of WordNet{'}s glosses, we propose a set of semantic roles that compose the semantic structure of a dictionary definition, and show how they are related to the definition{'}s syntactic configuration, identifying patterns that can be used in the development of information extraction frameworks and semantic models.
Corpus and dictionary development for classifiers/quantifiers towards a French-Japanese machine translation
Authors: Mutsuko Tomokiyo, Christian Boitet
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Machine Translation, Translation

Although quantifiers/classifiers expressions occur frequently in everyday communications or written documents, there is no description for them in classical bilingual paper dictionaries, nor in machine-readable dictionaries. The paper describes a corpus and dictionary development for quantifiers/classifiers, and their usage in the framework of French-Japanese machine translation (MT). They often cause problems of lexical ambiguity and of set phrase recognition during analysis, in particular for a long-distance language pair like French and Japanese. For the development of a dictionary aiming at ambiguity resolution for expressions including quantifiers and classifiers which may be ambiguous with common nouns, we have annotated our corpus with UWs (interlingual lexemes) of UNL (Universal Networking Language) found on the UNL-jp dictionary. The extraction of potential classifiers/quantifiers from corpus is made by UNLexplorer web service. Keywords : classifiers, quantifiers, phraseology study, corpus annotation, UNL (Universal Networking Language), UWs dictionary, Tori Bank, French-Japanese machine translation (MT).
An extension of ISO-Space for annotating object direction
Authors: Daiki Gotou, Hitoshi Nishikawa, Takenobu Tokunaga
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Object, TAG

In this paper, we extend an existing annotation scheme ISO-Space for annotating necessary spatial information for the task placing an specified object at a specified location with a specified direction according to a natural language instruction. We call such task the spatial placement problem. Our extension particularly focuses on describing the object direction, when the object is placed on the 2D plane. We conducted an annotation experiment in which a corpus of 20 situated dialogues were annotated. The annotation result showed the number of newly introduced tags by our proposal is not negligible. We also implemented an analyser that automatically assigns the proposed tags to the corpus and evaluated its performance. The result showed that the performance for entity tag was quite high ranging from 0.68 to 0.99 in F-measure, but not the case for relation tags, i.e. less than 0.4 in F-measure.
Annotation and Analysis of Discourse Relations, Temporal Relations and Multi-Layered Situational Relations in Japanese Texts
Authors: Kimi Kaneko, Saku Sugawara, Koji Mineshima, Daisuke Bekki
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Articles, Natural Language Inference, Question Answering, Text Summarization

This paper proposes a methodology for building a specialized Japanese data set for recognizing temporal relations and discourse relations. In addition to temporal and discourse relations, multi-layered situational relations that distinguish generic and specific states belonging to different layers in a discourse are annotated. Our methodology has been applied to 170 text fragments taken from Wikinews articles in Japanese. The validity of our methodology is evaluated and analyzed in terms of degree of annotator agreement and frequency of errors.
Developing Universal Dependencies for Mandarin Chinese
Authors: Herman Leung, Rafa{\"e}l Poiret, Tak-sum Wong, Xinying Chen, Kim Gerdes, John Lee
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: POS

This article proposes a Universal Dependency Annotation Scheme for Mandarin Chinese, including POS tags and dependency analysis. We identify cases of idiosyncrasy of Mandarin Chinese that are difficult to fit into the current schema which has mainly been based on the descriptions of various Indo-European languages. We discuss differences between our scheme and those of the Stanford Chinese Dependencies and the Chinese Dependency Treebank.
Developing Corpus of Lecture Utterances Aligned to Slide Components
Authors: Ryo Minamiguchi, Masatoshi Tsuchiya
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Text Summarization

The approach which formulates the automatic text summarization as a maximum coverage problem with knapsack constraint over a set of textual units and a set of weighted conceptual units is promising. However, it is quite important and difficult to determine the appropriate granularity of conceptual units for this formulation. In order to resolve this problem, we are examining to use components of presentation slides as conceptual units to generate a summary of lecture utterances, instead of other possible conceptual units like base noun phrases or important nouns. This paper explains our developing corpus designed to evaluate our proposing approach, which consists of presentation slides and lecture utterances aligned to presentation slide components.
VSoLSCSum: Building a Vietnamese Sentence-Comment Dataset for Social Context Summarization
Authors: Minh-Tien Nguyen, Dac Viet Lai, Phong-Khac Do, Duc-Vu Tran, Minh-Le Nguyen
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Learning-To-Rank, Sentence

This paper presents VSoLSCSum, a Vietnamese linked sentence-comment dataset, which was manually created to treat the lack of standard corpora for social context summarization in Vietnamese. The dataset was collected through the keywords of 141 Web documents in 12 special events, which were mentioned on Vietnamese Web pages. Social users were asked to involve in creating standard summaries and the label of each sentence or comment. The inter-agreement calculated by Cohen{'}s Kappa among raters after validating is 0.685. To illustrate the potential use of our dataset, a learning to rank method was trained by using a set of local and social features. Experimental results indicate that the summary model trained on our dataset outperforms state-of-the-art baselines in both ROUGE-1 and ROUGE-2 in social context summarization.
BCCWJ-DepPara: A Syntactic Annotation Treebank on the `Balanced Corpus of Contemporary Written Japanese'
Authors: Masayuki Asahara, Yuji Matsumoto
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Dependency Parsing

Paratactic syntactic structures are difficult to represent in syntactic dependency tree structures. As such, we propose an annotation schema for syntactic dependency annotation of Japanese, in which coordinate structures are split from and overlaid on bunsetsu-based (base phrase unit) dependency. The schema represents nested coordinate structures, non-constituent conjuncts, and forward sharing as the set of regions. The annotation was performed on the core data of {`}Balanced Corpus of Contemporary Written Japanese{'}, which comprised about one million words and 1980 samples from six registers, such as newspapers, books, magazines, and web texts.
SCTB: A Chinese Treebank in Scientific Domain
Authors: Chenhui Chu, Toshiaki Nakazawa, Daisuke Kawahara, Sadao Kurohashi
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Chinese Word Segmentation, Machine Translation, Translation

Treebanks are curial for natural language processing (NLP). In this paper, we present our work for annotating a Chinese treebank in scientific domain (SCTB), to address the problem of the lack of Chinese treebanks in this domain. Chinese analysis and machine translation experiments conducted using this treebank indicate that the annotated treebank can significantly improve the performance on both tasks. This treebank is released to promote Chinese NLP research in scientific domain.
Big Community Data before World Wide Web Era
Authors: Tomoya Iwakura, Tetsuro Takahashi, Akihiro Ohtani, Kunio Matsui
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12

This paper introduces the NIFTY-Serve corpus, a large data archive collected from Japanese discussion forums that operated via a Bulletin Board System (BBS) between 1987 and 2006. This corpus can be used in Artificial Intelligence researches such as Natural Language Processing, Community Analysis, and so on. The NIFTY-Serve corpus differs from data on WWW in three ways; (1) essentially spam- and duplication-free because of strict data collection procedures, (2) historic user-generated data before WWW, and (3) a complete data set because the service now shut down. We also introduce some examples of use of the corpus.
An Overview of BPPT's Indonesian Language Resources
Authors: Gunarso Gunarso, Hammam Riza
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Machine Translation, speech-recognition, Speech Recognition, Speech Synthesis, Translation

This paper describes various Indonesian language resources that Agency for the Assessment and Application of Technology (BPPT) has developed and collected since mid 80{'}s when we joined MMTS (Multilingual Machine Translation System), an international project coordinated by CICC-Japan to develop a machine translation system for five Asian languages (Bahasa Indonesia, Malay, Thai, Japanese, and Chinese). Since then, we have been actively doing many types of research in the field of statistical machine translation, speech recognition, and speech synthesis which requires many text and speech corpus. Most recent cooperation within ASEAN-IVO is the development of Indonesian ALT (Asian Language Treebank) has added new NLP tools.
Creating Japanese Political Corpus from Local Assembly Minutes of 47 prefectures
Authors: Yasutomo Kimura, Keiichi Takamaru, Takuma Tanaka, Akio Kobayashi, Hiroki Sakaji, Yuzu Uchida, Hokuto Ototake, Shigeru Masuyama
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12

This paper describes a Japanese political corpus created for interdisciplinary political research. The corpus contains the local assembly minutes of 47 prefectures from April 2011 to March 2015. This four-year period coincides with the term of office for assembly members in most autonomies. We analyze statistical data, such as the number of speakers, characters, and words, to clarify the characteristics of local assembly minutes. In addition, we identify problems associated with the different web services used by the autonomies to make the minutes available to the public.
Selective Annotation of Sentence Parts: Identification of Relevant Sub-sentential Units
Authors: Ge Xu, Xiaoyan Yang, Chu-Ren Huang
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Binary Classification, Opinion Mining, Sentence

Many NLP tasks involve sentence-level annotation yet the relevant information is not encoded at sentence level but at some relevant parts of the sentence. Such tasks include but are not limited to: sentiment expression annotation, product feature annotation, and template annotation for Q{\&}A systems. However, annotation of the full corpus sentence by sentence is resource intensive. In this paper, we propose an approach that iteratively extracts frequent parts of sentences for annotating, and compresses the set of sentences after each round of annotation. Our approach can also be used in preparing training sentences for binary classification (domain-related vs. noise, subjectivity vs. objectivity, etc.), assuming that sentence-type annotation can be predicted by annotation of the most relevant sub-sentences. Two experiments are performed to test our proposal and evaluated in terms of time saved and agreement of annotation.
The Kyutech corpus and topic segmentation using a combined method
Authors: Takashi Yamamura, Kazutaka Shimada, Shintaro Kawahara
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Decision Making, Segmentation

Summarization of multi-party conversation is one of the important tasks in natural language processing. In this paper, we explain a Japanese corpus and a topic segmentation task. To the best of our knowledge, the corpus is the first Japanese corpus annotated for summarization tasks and freely available to anyone. We call it {``}the Kyutech corpus.{''} The task of the corpus is a decision-making task with four participants and it contains utterances with time information, topic segmentation and reference summaries. As a case study for the corpus, we describe a method combined with LCSeg and TopicTiling for a topic segmentation task. We discuss the effectiveness and the problems of the combined method through the experiment with the Kyutech corpus.
Automatic Evaluation of Commonsense Knowledge for Refining Japanese ConceptNet
Authors: Seiya Shudo, Rafal Rzepka, Kenji Araki
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Common Sense Reasoning

In this paper we present two methods for automatic common sense knowledge evaluation for Japanese entries in ConceptNet ontology. Our proposed methods utilize text-mining approach: one with relation clue words and WordNet synonyms, and one without. Both methods were tested with a blog corpus. The system based on our proposed methods reached relatively high precision score for three relations (MadeOf, UsedFor, AtLocation), which is comparable with previous research using commercial search engines and simpler input. We analyze errors and discuss problems of common sense evaluation, both manual and automatic and propose ideas for further improvements.
SAMER: A Semi-Automatically Created Lexical Resource for Arabic Verbal Multiword Expressions Tokens Paradigm and their Morphosyntactic Features
Authors: Mohamed Al-Badrashiny, Abdelati Hawwari, Mahmoud Ghoneim, Mona Diab
Date: 2016-12-01 00:00:00
Proceeding: WS 2016 12
Tasks: Machine Translation, POS

Although MWE are relatively morphologically and syntactically fixed expressions, several types of flexibility can be observed in MWE, verbal MWE in particular. Identifying the degree of morphological and syntactic flexibility of MWE is very important for many Lexicographic and NLP tasks. Adding MWE variants/tokens to a dictionary resource requires characterizing the flexibility among other morphosyntactic features. Carrying out the task manually faces several challenges since it is a very laborious task time and effort wise, as well as it will suffer from coverage limitation. The problem is exacerbated in rich morphological languages where the average word in Arabic could have 12 possible inflection forms. Accordingly, in this paper we introduce a semi-automatic Arabic multiwords expressions resource (SAMER). We propose an automated method that identifies the morphological and syntactic flexibility of Arabic Verbal Multiword Expressions (AVMWE). All observed morphological variants and syntactic pattern alternations of an AVMWE are automatically acquired using large scale corpora. We look for three morphosyntactic aspects of AVMWE types investigating derivational and inflectional variations and syntactic templates, namely: 1) inflectional variation (inflectional paradigm) and calculating degree of flexibility; 2) derivational productivity; and 3) identifying and classifying the different syntactic types. We build a comprehensive list of AVMWE. Every token in the AVMWE list is lemmatized and tagged with POS information. We then search Arabic Gigaword and All ATBs for all possible flexible matches. For each AVMWE type we generate: a) a statistically ranked list of MWE-lexeme inflections and syntactic pattern alternations; b) An abstract syntactic template; and c) The most frequent form. Our technique is validated using a Golden MWE annotated list. The results shows that the quality of the generated resource is 80.04{\%}.