LEILA: Learning to Extract Information by Linguistic Analysis

What LEILA is

LEILA is a system that can extract pairs of a relation from a set of HTML documents. For example, it can extract pairs of persons with their birthdate, pairs of companies with their headquarters or pairs of entities with their concept. LEILA is part of the YAGO-NAGA project at the Max-Planck Institute for Informatics in Saarbrücken/Germany. LEILA is no longer actively maintained, so there is no more software support for it.

What LEILA needs

As input, LEILA needs a set of pairs that are in the relation (the examples) and a set of pairs that are not in the relation (the counterexamples). For instance, for the birthdate-relation, the examples could be

The counterexamples could be

The examples and counterexamples are given by a Java-method. This means that the counterexamples need not be enumerated. For instance, the Java-method can simply say that any pair of a person that is listed in the examples and a "wrong" birthdate is a counterexample.

How LEILA works

LEILA works in 3 phases:

1. It finds all sentences in which an example pair appears. It collects the pattern in which the example pair appears (the positive patterns). For instance, for the following sentence "Chopin was born in 1810", it would extract the pattern "X was born in Y". Then, LEILA runs again through the documents and finds all sentences in which a positive pattern matches (possibly approximately), but a counterexample stands in the place of X and Y. The corresponding pattern is collected as a negative pattern.
2. LEILA generalizes the positive patterns by machine learning techniques.
3. LEILA runs through the documents again and finds all sentences, in which a generalized positive pattern matches. It proposes the words in place of X and Y as a new pair. For example, if it finds the sentence "Vivaldi was born in 1678", it will propose the pair Vivaldi/1678. 

What is special about LEILA

The pattern matching approach is very simple and widely used. Different from previous systems, LEILA uses a deep linguistic analysis of the documents by the Link Grammar Parser. Thus, its patterns are deeper and more robust than simple surface patterns. Furthermore, LEILA bounds its patterns by counterexamples and generalizes them by machine learning.

Please find more information about LEILA in the tabs below.

• Main paper: "Combining Linguistic and Statistical Analysis to Extract Relations from Web Documents" (pdf, bib, Technical Report)
• "LEILA: Learning to Extract Information by Linguistic Analysis" (pdf, ppt, bib)

What this is

This is a set of corpora for relation extraction. Relation extraction is the task of, given a semantic target relation and given a natural language corpus, extracting all pairs of entities in the corpus that stand in the target relation. For example, if the target relation is instanceOf and the corpus contains the following passage

"President Mickey M. Mouse was happy to visit the city of Washington D.C., which is the capital of the United States."

then the goal is to extract the following pairs:

This web site provides corpora for evaluating Relation Extraction systems. For each document in the corpus, we provide a list of manually extracted ideal pairs that should be extracted by the system. Note that these pairs are not linked to the original sentence, but only to the document. The corpora were used with LEILA.

What types of files we have

The manually extracted pairs are licensed under the Creative Commons Attribution License by the author Fabian M. Suchanek. If you use them, please cite our paper. The other files are licensed under the GNU Free Documentation License, unless they underly different terms by their authors.  

Corpora