This repository contains Lucene tools (analysers, tokenizers and filters) for the Tibetan Language. They are based on these Lucene analyzers.
Content summary:
<dependency>
<groupId>io.bdrc.lucene</groupId>
<artifactId>lucene-bo</artifactId>
<version>1.5.0</version>
</dependency>
If the jar is needed for use in a non-maven based install, it may be found at
https://repo1.maven.org/maven2/io/bdrc/lucene/lucene-bo/1.2.0/lucene-bo-1.2.0.jar
First, make sure the submodule is initialized (git submodule init
, then git submodule update
from the root of the repo)
The base command line to build a jar is:
mvn clean compile exec:java package
The following options alter the packaging:
-DincludeDeps=true
includes io.bdrc.lucene:stemmer
and io.bdrc.ewtsconverter:ewts-converter
in the produced jar file-DperformRelease=true
signs the jar file with gpgThe main Analyzer. It tokenizes the input text using TibSyllableTokenizer, then applies TibAffixedFilter and StopFilter with a predefined list of stop words.
There are two constructors. The nullary constructor and
TibetanAnalyzer(boolean segmentInWords, boolean lemmatize, boolean filterChars, boolean fromEwts, String lexiconFileName)
segmentInWords - if the segmentation is on words instead of syllables
lemmatize - in syllable mode, possible values are "affix" (removes affixed particles), "paba" (normalizes ba/bo in pa/po), "verbs" (normalizes verbs in their present form) or any combination separated by hyphens (ex: "affix-paba-verbs"); in word segmentation the only possible value is "lemmas"
normalize - "none", "min" (same as lucene-bo 1.5.0, minimal normalization), "ot" (Old Tibetan, see below), "l" (lenient, see below), "otl" (Old Tibetan + Lenient)
inputMode - "unicode" (default), "ewts", "dts" (Diacritics Transliteration Schema) or "alalc" ([ALA-LC](https://www.loc.gov/catdir/cpso/romanization/tibetan.pdf))
stopFilename - file name of the stop word list (defaults to empty string for the shipped one, set to null for no stop words)
The nullary constructor is equivalent to TibetanAnalyzer(true, true, true, false, null)
In syllable lemmatization, the lemmatization of verbs is taken from a list of inflected verbs with their corresponding present form. It's been extracted from Hill, Nathan (2010) "A Lexicon of Tibetan Verb Stems as Reported by the Grammatical Tradition" (Munich: Bayerische Akademie der Wissenschaften, ISBN 978-3-7696-1004-8). The list is derived from the version on https://github.com/tibetan-nlp/lexicon-of-tibetan-verb-stems/, with very minor adjustments and reformatting.
The analyzer implements most of the patterns that have been listed in the context of Faggionato, C. & Garrett E., Constraint Grammars for Tibetan Language Processing, https://ep.liu.se/konferensartikel.aspx?series=&issue=168&Article_No=3 . The list of patterns can be found on https://github.com/tibetan-nlp/tibcg3/blob/master/Normalize_Old_Tibetan.txt .
This mode also normalizes the gigu to just one form, removes the dadrag, and the medial འ in the TibAffixedFilter (see below).
The lenient normalization normalizes a number of features that are found mostly in Sanskrit text and normalize them to more regular Tibetan features. One of the goals is that the search is less case sensitive in EWTS. This includes:
This tokenizer produces words through a Maximal Matching algorithm. It builds on top of this Trie implementation.
Due to its design, this tokenizer doesn't deal with contextual ambiguities.
For example, if both དོན and དོན་གྲུབ exist in the Trie, དོན་གྲུབ will be returned every time the sequence དོན + གྲུབ is found.
The sentence སེམས་ཅན་གྱི་དོན་གྲུབ་པར་ཤོག will be tokenized into "སེམས་ཅན + གྱི + དོན་གྲུབ + པར + ཤོག" (སེམས་ཅན + གྱི + དོན + གྲུབ་པར + ཤོག expected)
This mode removes the final འ when it's not necessary.
This tokenizer produces syllable tokens (with no tshek) from the input Tibetan text.
This filter removes non-ambiguous affixed particles (འི, འོ, འིའོ, འམ, འང and འིས), leaving the འ if necessary (ex: དགའི -> དགའ, གའི -> ག).
This filter normalizes བ and བོ into པ and པོ. It does not look into affixed particles and thus should be used after TibAffixedFilter
.
To sign the .jar
s before deploying, pass -DperformRelease=true
; to include ewts-converter
and stemmer
in the built jar, pass -DincludeDeps=true
.
The code is Copyright 2017 Buddhist Digital Resource Center, and is provided under Apache License 2.0.