Lucene Analyzers for Tibetan

This repository contains Lucene tools (analysers, tokenizers and filters) for the Tibetan Language. They are based on these Lucene analyzers.

Content summary:

• a convertor from EWTS, DTS or ALALC encodings to Tibetan Unicode
• a filter to normalise unicode Tibetan characters
• a filter to remove obvious affixed particles
• a stopword filter
• a syllable-based tokenizer
• a maxmatch-based word tokenizer that:
  • can lemmatize (remove ambiguous affixes ར and ས)
  • uses user-defined word lists

Installation through maven:

    <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

Building from source

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 gpg

Components

TibetanAnalyzer

The 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)

Syllable normalization

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.

Old Tibetan normalization

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).

Lenient normalization

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:

• retroflexes are "reversed": ཊ -> ཏ
• graphical variants are normalized: ཪ (fixed R form) -> ར (regular r)
• achung are removed
• gigus are normalized in one direction

TibWordTokenizer

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.

TibSyllableTokenizer

This tokenizer produces syllable tokens (with no tshek) from the input Tibetan text.

TibAffixedFilter

This filter removes non-ambiguous affixed particles (འི, འོ, འིའོ, འམ, འང and འིས), leaving the འ if necessary (ex: དགའི -> དགའ, གའི -> ག).

PaBaFilter

This filter normalizes བ and བོ into པ and པོ. It does not look into affixed particles and thus should be used after TibAffixedFilter.

Maven Build Options

To sign the .jars before deploying, pass -DperformRelease=true ; to include ewts-converter and stemmer in the built jar, pass -DincludeDeps=true.

License

The code is Copyright 2017 Buddhist Digital Resource Center, and is provided under Apache License 2.0.