Articles

People create morphs, a special type of fake alternative names, to achieve certain communication goals such as expressing strong sentiment or evading censors. For example, “Black Mamba”, the name for a highly venomous snake, is a morph that Kobe Bryant created for himself due to his agility and aggressiveness in …...

An event chronicle provides people with an easy and fast access to learn the past. In this paper, we propose the first novel approach to automatically generate a top- ically relevant event chronicle during a certain period given a reference chronicle during another period. Our approach con- sists of two …...

We study the problem of summarizing DAG-structured topic hierarchies over a given set of documents. Example appli- cations include automatically generating Wikipedia disambiguation pages for a set of articles, and generating candidate multi-labels for preparing machine learn- ing datasets (e.g., for text classification, functional genomics, and image classi- fication). Unlike …...

We study the problem of explaining re- lationships between pairs of knowledge graph entities with human-readable de- scriptions. Our method extracts and en- riches sentences that refer to an entity pair from a corpus and ranks the sentences ac- cording to how well they describe the re- lationship between the …...

While recent years have seen a surge of in- terest in automated essay grading, includ- ing work on grading essays with respect to particular dimensions such as prompt adherence, coherence, and technical qual- ity, there has been relatively little work on grading the essay dimension of argu- ment strength, which …...

We characterize a class of indirect an- swers to yes/no questions, alternative an- swers, where information is given that is not directly asked about, but which might nonetheless address the underlying moti- vation for the question. We develop a model rooted in game theory that gener- ates these answers via …...

Document enrichment focuses on retriev- ing relevant knowledge from external re- sources, which is essential because text is generally replete with gaps. Since conven- tional work primarily relies on special re- sources, we instead use triples of Subject, Predicate, Object as knowledge and in- corporate distributional semantics to rank them. …...

We propose that entity queries are gener- ated via a two-step process: users first se- lect entity facts that can distinguish tar- get entities from the others; and then choose words to describe each selected fact. Based on this query generation paradigm, we propose a new entity rep- resentation model …...

Non-linear models recently receive a lot of attention as people are starting to dis- cover the power of statistical and em- bedding features. However, tree-based models are seldom studied in the con- text of structured learning despite their re- cent success on various classification and ranking tasks. In this paper, …...

Spoken dialogue systems (SDS) typically require a predefined semantic ontology to train a spoken language understanding (SLU) module. In addition to the anno- tation cost, a key challenge for design- ing such an ontology is to define a coher- ent slot set while considering their com- plex relations. This paper …...

In natural language understanding (NLU), a user utterance can be labeled differently depending on the domain or application (e.g., weather vs. calendar). Standard domain adaptation techniques are not di- rectly applicable to take advantage of the existing annotations because they assume that the label set is invariant. We propose a …...

We propose an event-driven model for headline generation. Given an input document, the system identifies a key event chain by extracting a set of structural events that describe them. Then a novel multi-sentence compression algorithm is used to fuse the extracted events, generating a headline for the document. Our model …...

We present a new factoid-annotated dataset for evaluating content models for scientific survey article generation containing 3,425 sentences from 7 topics in natural language processing. We also introduce a novel HITS-based content model for automated survey article gen- eration called HITSUM that exploits the lexical network structure between sen- tences …...

Cross-lingual sentiment analysis is a task of identifying sentiment polarities of texts in a low-resource language by using sen- timent knowledge in a resource-abundant language. While most existing approaches are driven by transfer learning, their performance does not reach to a promising level due to the transferred errors. In this …...

The sentiment classification performance relies on high-quality sentiment resources. However, these resources are imbalanced in different languages. Cross-language sentiment classification (CLSC) can lever- age the rich resources in one language (source language) for sentiment classifica- tion in a resource-scarce language (target language). Bilingual embeddings could eliminate the semantic gap between …...

We present a novel syntax-based natural language generation system that is train- able from unaligned pairs of input mean- ing representations and output sentences. It is divided into sentence planning, which incrementally builds deep-syntactic de- pendency trees, and surface realization. Sentence planner is based on A* search with a perceptron …...

We propose a cross-lingual framework for fine-grained opinion mining using bitext projection. The only requirements are a running system in a source language and word-aligned parallel data. Our method projects opinion frames from the source to the target language, and then trains a sys- tem on the target language using …...

Semantic role labeling (SRL) is crucial to natural language understanding as it identi- fies the predicate-argument structure in text with semantic labels. Unfortunately, re- sources required to construct SRL models are expensive to obtain and simply do not exist for most languages. In this paper, we present a two-stage method …...

The last few years have seen a surge in the number of accurate, fast, publicly avail- able dependency parsers. At the same time, the use of dependency parsing in NLP applications has increased. It can be difficult for a non-expert to select a good “off-the-shelf” parser. We present a com- …...

Comparisons in text, such as in online re- views, serve as useful decision aids. In this paper, we focus on the task of iden- tifying whether a comparison exists be- tween a specific pair of entity mentions in a sentence. This formulation is trans- formative, as previous work only seeks …...