Open domain relation extraction systems identify relation and argument phrases in a sentence without relying on any underlying schema. However, current state-of-the-art relation extraction systems are available only for English because of their heavy reliance on linguistic tools such as part-of-speech taggers and dependency parsers. We present a cross-lingual annotation projection method for la...

The modern concept of the spread of tuberculosis from an open case to a susceptible person dates back to pre-Koch times. Hippocrates, Sylvius and others recognized the infectious nature of tuberculosis long before Koch discovered the tubercle bacillus, but their understanding of the nature of infection was at best vague. Koch's discovery gave point to the infectious nature of the disease. In hi...

One of the most accurate methods in Question Answering uses off-line information extraction to find answers for frequently asked questions. It requires automatic extraction from text of all relation instances for relations that users frequently ask for. In this chapter, we present two methods for learning relation instances for relations relevant in a closed and open domain (medical) question a...

We propose CORE, a novel matrix factorization model that leverages contextual information for open relation extraction. Our model is based on factorization machines and integrates facts from various sources, such as knowledge bases or open information extractors, as well as the context in which these facts have been observed. We argue that integrating contextual information—such as metadata abo...

Open Relation Extraction (ORE) overcomes the limitations of traditional IE techniques, which train individual extractors for every single relation type. Systems such as ReVerb, PATTY, OLLIE, and Exemplar have attracted much attention on English ORE. However, few studies have been reported on ORE for languages beyond English. This paper presents a syntax-based Chinese (Zh) ORE system, ZORE, for ...

Open Information Extraction has shown promise of overcoming a knowledge engineering bottleneck, but has a fundamental limitation. It is unable to extract implicit relations, where the sentence lacks an explicit relation phrase. We present IMPLIE (Implicit relation Information Extraction) that uses an open-domain syntactic language model and user-supplied semantic taggers to overcome this limita...

in a recent paper, de baets et al. have characterized the fuzzytolerance and fuzzy equivalence relations that a given strict order relation iscompatible with. in this paper, we generalize this characterization by consideringan arbitrary (crisp) relation instead of a strict order relation, while payingattention to the particular cases of a reflexive or irreflexive relation. the reasoninglargely ...

Negative facts in relational databases have traditionally been inferred using the closed world assumption. There are situations where this is not appropriate. We need to resort to the open world assumption, where the negative facts are sometimes explicitly stated. We present a formalism which is capable of answering queries in the relational database context under the open world assumption. We ...