The task of entity retrieval becomes increasingly prevalent as more and more structured information about entities is available on the Web in various forms such as documents embedding metadata (RDF, RDFa, Microdata, Microformats). International benchmarking campaigns, e.g., the Text REtrieval Conference or the Semantic Search Challenge, propose entity-oriented search tracks. This reflects the n...

This paper describes the systems of THU QUANTA in Text Analysis Conference (TAC) 2009. We participated in the Knowledge Base Population (KBP) track, and the Recognizing Textual Entailment (RTE) track. For the KBP track, we investigate two ranking strategies for Entity Linking task. We employ a Listwise “Learning to Rank” model and Augmenting Naïve Bayes model to rank the candidate. We try to us...

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 TAC-KBP program, the entity linking task is considered as independent from or a pre-processing step of the slot filling task. Previous efforts on this task mainly focus on utilizing the entity surface information and the...

Recent studies indicate that nearly 75% of queries issued to Web search engines aim at finding information about entities, which are material objects or concepts that exist in the real world or fiction (e.g. people, organizations, products, etc.). Most common information needs underlying this type of queries include finding a certain entity (e.g. “Einstein relativity theory”), a particular attr...

In open domain table-to-text generation, we notice the unfaithful generation usually contains hallucinated entities which can not be aligned to any input table record. We thus try evaluate faithfulness with two entity-centric metrics: record coverage and ratio of in text, both are shown have strong agreement human judgements. Then based on these metrics, quantitatively analyze correlation betwe...

Entity and relation linking are the core tasks in knowledge base question answering (KBQA). They connect natural language questions with triples base. In most studies, researchers perform these two independently, which ignores interplay between entity linking. To address above problems, some have proposed a framework for joint based on feature multi-attention. this paper, their method, we offer...

The TREC Entity track aimed to build test collections to evaluate entity-oriented search on Web data. In 2011, the track worked with two corpora: the ClueWeb 2009 web corpus and the new Sindice-2011 dataset [2]. Motivated by observations from the 2010 Entity track, we made the following changes in the track setup for 2011. In the REF task, we focused on modifications to simplify the evaluation ...

The goal of our participation in TREC 2005 was to determine how effectively our entity recognition/text analysis system, Lydia (http://www.textmap.com) [1–3] could be adapted to question answering. Indeed, our entire QA subsystem consists of only about 2000 additional lines of Perl code. Lydia detects every named entity mentioned in the AQUAINT corpus, and keeps a variety of information on name...

Personalized ranking is a typical task of recommender systems. It can provide a set of items for specific user and help recommender systems more correctly direct each item to its user. Recently, as the dramatically increasing social media, an entity, i.e., user and item, usually associates with multiple kinds of characterized information, e.g., explicit ratings, implicit feedbacks, and multi-ty...

In this paper, we present our strategy for TREC 2014 KBA track Vital Filtering task. This task is also known as "Cumulative Citation Recommendation" or "CCR" in 2012 and 2013. Vital Filtering task is to identify "vital" documents containing timely and new information that should be used to update the profile of a given entity (also called a topic). Our strategy for vital filtering is to first r...