tree: 577e0639f8fd296747c062b825bfcbff16960427 [path history] [tgz]
  1. src/
  2. capabilities.org
  3. Changes
  4. korap-style.xml
  5. LICENSE
  6. pom.xml
  7. Readme.md
Readme.md

Krill

A Corpus Retrieval Index using Lucene for Look-Ups

Synopsis

Description

Krill is a Lucene based search engine for large annotated corpora, developed at the Institute for German Language (IDS) in Mannheim, Germany.

Features

Krill is the reference implementation for the KoralQuery protocol, covering most of its query features, including ...

Fulltext search

"Find all occurrences of the phrase 'sea monster'!"

"Find all case-insensitive words matching the regular expression /krak.*/"

Token-based annotation search

"Find all plural nouns in accusative!"

Span-based annotation search

"Find all nominal phrases!"

Distance search

...

Positional search

...

Nested queries

...

Multiple annotation resources

"Find all words marked as a noun by TreeTagger and marked as an adjective by CoreNLP](https://github.com/stanfordnlp/CoreNLP)!"

and many more ...

Virtual Collections; partial highlightings; Support for overlapping spans; relational queries; hierarchical queries ...

Prerequisites

...

Setup

$ git clone https://github.com/KorAP/Krill $ cd Krill

To run the test suite, type in ...

$ mvn test

To start the server, type in ...

$ mvn compile exec:java

To compile and run the indexer, type ...

$ mvn compile assembly:single

$ java -jar target/KorAP-krill-X.XX.jar src/main/resources/korap.conf src/test/resources/examples/

Development and License

Authors: Nils Diewald, Eliza Margaretha

Copyright 2013-2015, IDS Mannheim, Germany

Krill is developed as part of the KorAP Corpus Analysis Platform at the Institute for German Language (IDS).

For recent changes and compatibility issues, please consult the Changes file.

Krill is published under the BSD-2 License.

To cite this work, please ...

References and bundled Software

Named entities annotated in the test data by CoreNLP were using models based on:

Manaal Faruqui and Sebastian Padó (2010): Training and Evaluating a German Named Entity Recognizer with Semantic Generalization, Proceedings of KONVENS 2010, Saarbrücken, Germany