Articles

A new approach to large-scale information extraction exploits both Web documents and query logs to acquire thousands of open- domain classes of instances, along with rel- evant sets of open-domain class attributes at precision levels previously obtained only on small-scale, manually-assembled classes. 1...

Traditional Information Extraction (IE) takes a relation name and hand-tagged examples of that relation as input. Open IE is a relation- independent extraction paradigm that is tai- lored to massive and heterogeneous corpora such as the Web. An Open IE system extracts a diverse set of relational tuples from text …...

We present an automatic approach to deter- mining whether a pronoun in text refers to a preceding noun phrase or is instead non- referential. We extract the surrounding tex- tual context of the pronoun and gather, from a large corpus, the distribution of words that occur within that context. We …...

In this paper, we describe a system by which the multilingual characteristics of Wikipedia can be utilized to annotate a large corpus of text with Named Entity Recognition (NER) tags requiring minimal human intervention and no linguistic expertise. This process, though of value in languages for which resources exist, is …...

Active learning is well-suited to many prob- lems in natural language processing, where unlabeled data may be abundant but annota- tion is slow and expensive. This paper aims to shed light on the best active learning ap- proaches for sequence labeling tasks such as information extraction and document segmen- tation. …...

This paper presents a novel, ranking-style word segmentation approach, called RSVM- Seg, which is well tailored to Chinese informa- tion retrieval(CIR). This strategy makes seg- mentation decision based on the ranking of the internal associative strength between each pair of adjacent characters of the sentence. On the training corpus composed …...

We present a novel method for discovering and modeling the relationship between in- formal Chinese expressions (including collo- quialisms and instant-messaging slang) and their formal equivalents. Specifically, we pro- posed a bootstrapping procedure to identify a list of candidate informal phrases in web corpora. Given an informal phrase, we re- …...

We demonstrate the effectiveness of multilin- gual learning for unsupervised part-of-speech tagging. The key hypothesis of multilin- gual learning is that by combining cues from multiple languages, the structure of each be- comes more apparent. We formulate a hier- archical Bayesian model for jointly predicting bilingual streams of part-of-speech tags. …...

Web-search queries are known to be short, but little else is known about their structure. In this paper we investigate the applicability of part-of-speech tagging to typical English- language web search-engine queries and the potential value of these tags for improving search results. We begin by identifying a set of …...

Bootstrapping has a tendency, called seman- tic drift, to select instances unrelated to the seed instances as the iteration proceeds. We demonstrate the semantic drift of bootstrap- ping has the same root as the topic drift of Kleinberg’s HITS, using a simplified graph- based reformulation of bootstrapping. We confirm that …...

The accuracy of current word sense disam- biguation (WSD) systems is affected by the fine-grained sense inventory of WordNet as well as a lack of training examples. Using the WSD examples provided through OntoNotes, we conduct the first large-scale WSD evalua- tion involving hundreds of word types and tens of …...

Some phrases can be interpreted either id- iomatically (figuratively) or literally in con- text, and the precise identification of idioms is indispensable for full-fledged natural lan- guage processing (NLP). To this end, we have constructed an idiom corpus for Japanese. This paper reports on the corpus and the re- sults …...

Code-switching is an interesting linguistic phenomenon commonly observed in highly bilingual communities. It consists of mixing languages in the same conversational event. This paper presents results on Part-of-Speech tagging Spanish-English code-switched dis- course. We explore different approaches to exploit existing resources for both languages that range from simple heuristics, to …...

Knowing the degree of antonymy between words has widespread applications in natural language processing. Manually-created lexi- cons have limited coverage and do not include most semantically contrasting word pairs. We present a new automatic and empirical mea- sure of antonymy that combines corpus statis- tics with the structure of a …...

Predicting possible code-switching points can help develop more accurate methods for au- tomatically processing mixed-language text, such as multilingual language models for speech recognition systems and syntactic an- alyzers. We present in this paper exploratory results on learning to predict potential code- switching points in Spanish-English. We trained different learning …...

We describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. The key aspects of this problem are the design of a di- alog information representation and a learning approach that supports capture of domain in- formation from in-domain …...

This paper explores the use of set expan- sion (SE) to improve question answering (QA) when the expected answer is a list of entities belonging to a certain class. Given a small set of seeds, SE algorithms mine textual re- sources to produce an extended list including additional members of …...

An increasingly popular method for finding information online is via the Community Question Answering (CQA) portals such as Yahoo! An- swers, Naver, and Baidu Knows. Searching the CQA archives, and rank- ing, filtering, and evaluating the sub- mitted answers requires intelligent processing of the questions and an- swers posed by …...

Question classification plays an important role in question answering. Features are the key to obtain an accurate question classifier. In con- trast to Li and Roth (2002)’s approach which makes use of very rich feature space, we pro- pose a compact yet effective feature set. In particular, we propose head …...

This paper presents a graph-theoretic model of the acquisition of lexical syntactic representa- tions. The representations the model learns are non-categorical or graded. We propose a new evaluation methodology of syntactic ac- quisition in the framework of exemplar theory. When applied to the CHILDES corpus, the evaluation shows that the …...