Abstract: Generating a table of contents from a computer document is disclosed. The computer document is converted into a markup language, from which a list of grouped textblocks is generated. Headings are detected from among the list of grouped textblocks. For a grouped textblock, a first vector corresponding to a semantic representation of the grouped textblock and a second vector based on evaluation of pre-defined features in the grouped textblock are generated. Based on the first and second vectors, the grouped textblock is classified as a heading or a plain-text using a trained classifier.

Abstract: Generating a table of contents from a computer document is disclosed. The computer document is converted into a markup language, from which a list of grouped textblocks is generated. Headings are detected from among the list of grouped textblocks. For a grouped textblock, a first vector corresponding to a semantic representation of the grouped textblock and a second vector based on evaluation of pre-defined features in the grouped textblock are generated. Based on the first and second vectors, the grouped textblock is classified as a heading or a plain-text using a trained classifier.

Abstract: Methods, systems, and computer program products for extracting from a descriptive document the value of a slot associated with a target entity described in the descriptive document are disclosed. The descriptive document is split into a set of sentences, and the sentences are filtered to generate a set of candidate sentences. Candidate sentence-entity pairs are determined from the candidate sentences, where each candidate sentence-entity pair includes a candidate sentence and an associated entity of the same type as the slot. The candidate sentence-entity pairs are compared to a set of gold sentences associated with the slot to calculate a plurality of similarity measures. A candidate sentence-entity pair associated with a maximum similarity measure is determined, and the value of the associated entity of the determined candidate sentence-entity pair is assigned to the slot.

Abstract: Methods, systems, and computer program products for extracting from a descriptive document the value of a slot associated with a target entity described in the descriptive document are disclosed. The descriptive document is split into a set of sentences, and the sentences are filtered to generate a set of candidate sentences. Candidate sentence-entity pairs are determined from the candidate sentences, where each candidate sentence-entity pair includes a candidate sentence and an associated entity of the same type as the slot. The candidate sentence-entity pairs are compared to a set of gold sentences associated with the slot to calculate a plurality of similarity measures. A candidate sentence-entity pair associated with a maximum similarity measure is determined, and the value of the associated entity of the determined candidate sentence-entity pair is assigned to the slot.