Cognitive research indicates that abstraction ability is essential in human intelligence, which
remains under-explored in language models. In this paper, we present AbsPyramid, a …

Typed entailment graphs try to learn the entailment relations between predicates from text
and model them as edges between predicate nodes. The construction of entailment graphs …

Time information plays an important role in the areas of data mining, information retrieval,
and natural language processing. Among the linguistic tasks related to time expressions …

Language provides speakers with a rich system of modality for expressing thoughts about
events, without being committed to their actual occurrence. Modality is commonly used in the …

The diversity and Zipfian frequency distribution of natural language predicates in corpora
leads to sparsity in Entailment Graphs (EGs) built by Open Relation Extraction (ORE). EGs …

Abstraction ability is crucial in human intelligence, which can also benefit various tasks in
NLP study. Existing work shows that LLMs are deficient in abstract ability, and how to …

An open-domain knowledge graph (KG) has entities as nodes and natural language
relations as edges, and is constructed by extracting (subject, relation, object) triples from …

Typologically diverse languages offer systems of lexical and grammatical aspect that allow
speakers to focus on facets of event structure in ways that comport with the specific …

Entailment Graphs (EGs) have been constructed based on extracted corpora as a strong
and explainable form to indicate context-independent entailment relations in natural …

Understanding linguistic modality is widely seen as important for downstream tasks such as
Question Answering and Knowledge Graph Population. Entailment Graph learning might …