Supervised Models

Most coreference resolution models determine if two mentions are coreferent using a single function over a set of constraints or features. This approach can lead to incorrect decisions as lower …...

In this paper, we formulate extractive summarization as a risk minimization problem and propose a unified probabilis- tic framework that naturally combines su- pervised and unsupervised summarization models to inherit …...

Pathology reports are used to store infor- mation about cells and tissues of a patient, and they are crucial to monitor the health of individuals and population groups. In this …...

Sentence compression techniques often assemble output sentences using frag- ments of lexical sequences such as n- grams or units of syntactic structure such as edges from a dependency tree repre- …...

This paper explores to what extent lemmati- sation, lexical resources, distributional seman- tics and paraphrases can increase the accuracy of supervised models for dialogue manage- ment. The results suggest that …...

We propose a brand new “Liberal” Event Extraction paradigm to extract events and discover event schemas from any input corpus simultaneously. We incorporate symbolic (e.g., Abstract Meaning Repre- sentation) and …...

AbstractWord Sense Disambiguation models exist in many flavors. Even though supervised ones tend to perform best in terms of accuracy, they often lose ground to more flexible knowledge-based solutions, which …...

AbstractSeveral datasets have been annotated and published for classification of emotions. They differ in several ways: (1) the use of different annotation schemata (e. g., discrete label sets, including joy, …...

AbstractThis paper introduces open-domain event detection, a new event detection paradigm to address issues of prior work on restricted domains and event annotation. The goal is to detect all kinds …...

AbstractUsage similarity estimation addresses the semantic proximity of word instances in different contexts. We apply contextualized (ELMo and BERT) word and sentence embeddings to this task, and propose supervised models …...

AbstractSupervised models for Relation Extraction (RE) typically require human-annotated training data. Due to the limited size, the human-annotated data is usually incapable of covering diverse relation expressions, which could limit …...

AbstractCommitments and requests are a hallmark of collaborative communication, especially in team settings. Identifying specific tasks being committed to or request from emails and chat messages can enable important downstream …...

AbstractWe focus on the task of Frequently Asked Questions (FAQ) retrieval. A given user query can be matched against the questions and/or the answers in the FAQ. We present a …...

AbstractIn this paper, we present the first comprehensive categorization of essential commonsense knowledge for answering the Winograd Schema Challenge (WSC). For each of the questions, we invite annotators to first …...

AbstractDisambiguation of word senses in context is easy for humans, but is a major challenge for automatic approaches. Sophisticated supervised and knowledge-based models were developed to solve this task. However, …...

AbstractThe framing of political issues can influence policy and public opinion. Even though the public plays a key role in creating and spreading frames, little is known about how ordinary …...

AbstractBeing able to accurately perform Question Difficulty Estimation (QDE) can improve the accuracy of students’ assessment and better their learning experience. Traditional approaches to QDE are either subjective or introduce …...

AbstractCurrent question answering (QA) systems primarily consider the single-answer scenario, where each question is assumed to be paired with one correct answer. However, in many real-world QA applications, multiple answer …...

AbstractWe propose a generative model for text generation, which exhibits disentangled latent representations of syntax and semantics. Contrary to previous work, this model does not need syntactic information such as …...

AbstractUnderstanding what leads to emotions during large-scale crises is important as it can provide groundings for expressed emotions and subsequently improve the understanding of ongoing disasters. Recent approaches trained supervised …...