id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_osxqmwo2yjakvpw3wcmliie4ri	Jayant Krishnamurthy	Learning a Compositional Semantics for Freebase with an Open Predicate Vocabulary	2015	14	.pdf	application/pdf	8990	978	59	produce denotations for phrases such as "Republican front-runner from Texas" whose semantics cannot be represented using the Freebase schema. A training phase produces this probabilistic database using a corpus of entitylinked text and probabilistic matrix factorization with a novel ranking objective function. right: evaluating the logical form on the probabilistic database computes the marginal probability that each to map entity-linked texts to logical forms containing predicates derived from the words in the text. collect training data by analyzing entity-linked sentences in a large web corpus with the rule-based This process generates a collection of logical form queries with observed entity answers. From this simplified logical form, we generate two types of training data: (1) predicate instances, and (2) queries with known answers (see We generate two types of training data, predicate instances and queries with observed answers, by semantically parsing the sentence and	./cache/work_osxqmwo2yjakvpw3wcmliie4ri.pdf	./txt/work_osxqmwo2yjakvpw3wcmliie4ri.txt