Articles

AbstractISLEX is a multilingual Scandinavian dictionary, with Icelandic as a source language and Danish, Norwegian, Swedish, Faroese and Finnish as target languages. Within ISLEX are in fact contained several independent, bilingual dictionaries. While Faroese and Finnish are still under construction, the other languages were opened to the public on the …...

AbstractThis paper describes the integration of the Index Thomisticus Treebank (IT-TB) into the web-based treebank search and visualization application TueNDRA (Tuebingen aNnotated Data Retrieval & Analysis). TueNDRA was originally designed to provide access via the Internet to constituency treebanks and to tools for searching and visualizing them, as well as …...

AbstractComputational power needs have grown dramatically in recent years. This is also the case in many language processing tasks, due to overwhelming quantities of textual information that must be processed in a reasonable time frame. This scenario has led to a paradigm shift in the computing architectures and large-scale data …...

AbstractWe introduce a new formal semantic model for annotating textual entailments that describes restrictive, intersective, and appositive modification. The model contains a formally defined interpreted lexicon, which specifies the inventory of symbols and the supported semantic operators, and an informally defined annotation scheme that instructs annotators in which way to …...

AbstractRecent implementations of Natural Logic (NLog) have shown that NLog provides a quite direct means of going from sentences in ordinary language to many of the obvious entailments of those sentences. We show here that Episodic Logic (EL) and its Epilog implementation are well-adapted to capturing NLog-like inferences, but beyond …...

AbstractThe relational syllogistic is an extension of the language of Classical syllogisms in which predicates are allowed to feature transitive verbs with quantified objects. It is known that the relational syllogistic does not admit a finite set of syllogism-like rules whose associated (direct) derivation relation is sound and complete. We …...

AbstractThis paper serves two purposes. It is a summary of much work concerning formal treatments of monotonicity and polarity in natural language, and it also discusses connections to related work on exclusion relations, and connections to psycholinguistics and computational linguistics. The second part of the paper presents a summary of …...

AbstractThe role of inference as it relates to natural language (NL) semantics has often been neglected. Recently, there has been a move away by some NL semanticists from the heavy machinery of, say, Montagovianstyle semantics to a more proof-based approach. Although researchers tend to study each type of system independently, …...

AbstractClassical intensional semantic frameworks, like Montague’s Intensional Logic (IL), identify intensional identity with logical equivalence. This criterion of co-intensionality is excessively coarse-grained, and it gives rise to several well-known difficulties. Theories of fine-grained intensionality have been been proposed to avoid this problem. Several of these provide a formal solution to …...

AbstractThe lexicon of any natural language encodes a huge number of distinct word meanings. Just to understand this article, you will need to know what thousands of words mean. The space of possible sentential meanings is infinite: In this article alone, you will encounter many sentences that express ideas you …...

AbstractBeside formal approaches to semantic inference that rely on logical representation of meaning, the notion of Textual Entailment (TE) has been proposed as an applied framework to capture major semantic inference needs across applications in Computational Linguistics. Although several approaches have been tried and evaluation campaigns have shown improvements in …...

AbstractFrom a purely theoretical point of view, it makes sense to approach recognizing textual entailment (RTE) with the help of logic. After all, entailment matters are all about logic. In practice, only few RTE systems follow the bumpy road from words to logic. This is probably because it requires a …...

AbstractRecent progress in research of the Recognizing Textual Entailment (RTE) task shows a constantly-increasing level of complexity in this research field. A way to avoid having this complexity becoming a barrier for researchers, especially for new-comers in the field, is to provide a freely available RTE system with a high …...

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 entities). Our model is formally a structured conditional random field. Unary factors encode local features from strong baselines for each …...

AbstractAdaptor grammars are a flexible, powerful formalism for defining nonparametric, unsupervised models of grammar productions. This flexibility comes at the cost of expensive inference. We address the difficulty of inference through an online algorithm which uses a hybrid of Markov chain Monte Carlo and variational inference. We show that this …...

AbstractAnnotated data is prerequisite for many NLP applications. Acquiring large-scale annotated corpora is a major bottleneck, requiring significant time and resources. Recent work has proposed turning annotation into a game to increase its appeal and lower its cost; however, current games are largely text-based and closely resemble traditional annotation tasks. …...

AbstractThis paper identifies and examines the key principles underlying building a state-of-the-art grammatical error correction system. We do this by analyzing the Illinois system that placed first among seventeen teams in the recent CoNLL-2013 shared task on grammatical error correction. The system focuses on five different types of errors common …...

AbstractWe present a polynomial-time parsing algorithm for CCG, based on a new decomposition of derivations into small, shareable parts. Our algorithm has the same asymptotic complexity, O(n6), as a previous algorithm by Vijay-Shanker and Weir (1993), but is easier to understand, implement, and prove correct....

AbstractLinear models, which support efficient learning and inference, are the workhorses of statistical machine translation; however, linear decision rules are less attractive from a modeling perspective. In this work, we introduce a technique for learning arbitrary, rule-local, non-linear feature transforms that improve model expressivity, but do not sacrifice the efficient …...

AbstractIn this paper we introduce a novel semantic parsing approach to query Freebase in natural language without requiring manual annotations or question-answer pairs. Our key insight is to represent natural language via semantic graphs whose topology shares many commonalities with Freebase. Given this representation, we conceptualize semantic parsing as a …...