In this paper we give an overview of the Knowledge Base Population (KBP) track at the 2010
Text Analysis Conference. The main goal of KBP is to promote research in discovering facts …

Relation triples produced by open domain information extraction (open IE) systems are
useful for question answering, inference, and other IE tasks. Traditionally these are extracted …

In this paper we give an overview of the Knowledge Base Population (KBP) track at TAC
2011. The main goal of KBP is to promote research in discovering facts about entities and …

Broad-coverage relation extraction either requires expensive supervised training data, or
suffers from drawbacks inherent to distant supervision. We present an approach for …

The CUNY-BLENDER team participated in the following tasks in TAC-KBP2010: Regular
Entity Linking, Regular Slot Filling and Surprise Slot Filling task (per: disease slot). In the …

Traditionally, pattern-based relation extraction methods are usually based on iterative
bootstrapping model which generally implies semantic drift or low recall problem. In this …

The NYU Knowledge Base Population (KBP) slot filling system for 2011 was built upon the
system for 2010. The primary addition was a set of classifiers trained using distant …

Abstract The Knowledge Based Population (KBP) evaluation track of the Text Analysis
Conferences (TAC) has been held for the past 3 years. One of the two tasks of KBP is slot …

Abstract Our method to Knowledge Base Population at TAC2011 is described in this paper.
Rule-based method and machine learning method are combined in the Slot Filling task. And …

The increasing availability of large text corpora holds the promise of acquiring an
unprecedented amount of knowledge from this text. However, current techniques are either …