akana-cli 0.11.0

CLI utility for Akana Turkish NLP toolkit
THIRD-PARTY NOTICES

akana is distributed under the MIT License or the Apache License 2.0, at your option. It
contains, or is built from, the third-party material listed here. Every shipped file derived
from such material is named with its source, licence and changes. A file derived from data
under CC BY-SA is marked "DERIVED FROM CC BY-SA DATA", and the CC BY-SA terms apply to that
file.

The sources akana's tools may download are pinned, with the licence each one states, in
scripts/morph_sources.json. A source appears below only once something derived from it ships.

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1. Zemberek dictionaries (zemberek-nlp)
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Source:     https://github.com/ahmetaa/zemberek-nlp, morphology/src/main/resources/tr (the default
            dictionaries of TurkishDictionaryLoader), as copied unmodified into Zeyrek 0.1.3.
            Vendored in scripts/lexicon/zemberek/ (see NOTICE.md there for checksums).
Copyright:  Ahmet A. Akın and the zemberek-nlp contributors.
Licence:    Apache License 2.0 (full text at the end of this file).

Shipped as: crates/akana-core/src/morphology/zemberek_lexicon.txt, compiled into the library.
            scripts/build_full_lexicon.py builds it from the Zemberek dictionaries.
Changes:    duplicate entries merged; corpus-collected proper nouns that are inflected common
            words or common words without their Turkish letters, and roots with stray
            characters, dropped; Zemberek's Ref: pointers made lemmas; entries added, replaced,
            respelled and removed by akana's own supplements (scripts/lexicon/akana-legal.dict,
            akana-extra.dict, akana-variants.dict, akana-names.dict, akana-spelling.dict,
            akana-remove.dict, which carry akana's own attributes Lexicalized,
            NotLexicalized, Rare and Nonstandard); homographs numbered; written in akana's
            one-line format.

Shipped as: crates/akana-core/src/pii/person_names.txt, compiled into the library: the given
            names of Zemberek's person-names.dict (morphology/src/main/resources/tr), which PII
            masking reads as first names.
Changes:    lower-cased with Turkish rules; forms without circumflexes added.

The morphotactics (crates/akana-core/src/morphology/turkish_morphotactics.rs, stems.rs,
analyzer.rs) port the design of zemberek-nlp's TurkishMorphotactics, StemTransitionsBase and
RuleBasedAnalyzer (Apache License 2.0) to Rust.

crates/akana-core/tests/data/morphology/review/zemberek_tests.tsv is test data, not compiled
into the library. It is part of the source repository and of the crate's source package. It
holds the analysis checks of zemberek-nlp's morphology tests
(morphology/src/test/java/zemberek/morphology/analysis, Apache License 2.0). They were
converted to one check per line, and their dictionary lines were rewritten in akana's
lexicon format.

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2. Universal Dependencies Turkish treebanks BOUN, Kenet, Penn, Tourism, Atis and FrameNet
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Source:     https://github.com/UniversalDependencies/UD_Turkish-BOUN, UD_Turkish-Kenet,
            UD_Turkish-Penn, UD_Turkish-Tourism, UD_Turkish-Atis and UD_Turkish-FrameNet,
            release r2.18: the train and dev splits (no test split).
Authors:    BOUN: Büşra Marşan, Furkan Akkurt, Utku Türk, Furkan Atmaca, Şaziye Betül Özateş,
            Gözde Berk, Seyyit Talha Bedir, Abdullatif Köksal, Balkız Öztürk Başaran, Tunga
            Güngör, Arzucan Özgür (Türk et al. 2022, "Resources for Turkish Dependency Parsing:
            Introducing the BOUN Treebank and the BoAT Annotation Tool", Language Resources and
            Evaluation 56(1), doi:10.1007/s10579-021-09558-0; Marşan et al. 2022,
            arXiv:2207.11782). Kenet: Aslı Kuzgun, Neslihan Cesur, Olcay Taner Yıldız, Oğuzhan
            Kuyrukçu, Arife Betül Yenice, Bilge Nas Arıcan, Ezgi Sanıyar. Penn: Neslihan Cesur,
            Aslı Kuzgun, Olcay Taner Yıldız, Büşra Marşan, Neslihan Kara, Bilge Nas Arıcan, Merve
            Özçelik, Deniz Baran Aslan. Tourism: Aslı Kuzgun, Neslihan Cesur, Olcay Taner Yıldız,
            Oğuzhan Kuyrukçu, Büşra Marşan, Bilge Nas Arıcan, Neslihan Kara, Deniz Baran Aslan,
            Ezgi Sanıyar, Cengiz Asmazoğlu. Atis: Mehmet Köse, Olcay Taner Yıldız. FrameNet:
            Neslihan Cesur, Aslı Kuzgun, Olcay Taner Yıldız, Büşra Marşan, Oğuzhan Kuyrukçu,
            Bilge Nas Arıcan, Ezgi Sanıyar, Neslihan Kara, Merve Özçelik (Marşan et al. 2021,
            "Building the Turkish FrameNet", Proceedings of the 11th Global Wordnet Conference,
            118-125).
Licence:    Creative Commons Attribution-ShareAlike 4.0 International,
            https://creativecommons.org/licenses/by-sa/4.0/legalcode

Shipped as: crates/akana-core/src/embeddings/function_lemmas.tsv, compiled into the library.
            DERIVED FROM CC BY-SA DATA: it is distributed under CC BY-SA 4.0.
Changes:    no text is shipped. The table holds, for 20 lemmas, the number of 256-token chunks
            of the BOUN and Kenet sentences (and of a court-decision sample) each occurs in, and
            the weight akana gives it (examples/sparse_idf.rs).

Shipped as: crates/akana-core/src/morphology/prior.tsv.gz, compiled into the library.
            DERIVED FROM CC BY-SA DATA: it is distributed under CC BY-SA 4.0.
Changes:    no text is shipped. The analyzer's frequency prior is estimated
            (examples/morph_prior.rs) from a court-decision word list mixed with the word
            counts of the six treebanks' sentences, with the words the analyzer reads in more
            than one part of speech split among them as the treebanks tag them, and per-word
            corrections that keep those shares. Both inputs are part of the source repository
            and also DERIVED FROM CC BY-SA DATA: data/morphology/prior_general_types.tsv.gz
            (scripts/prior_general_types.py: each word of the sentences and how often it
            occurs) and data/morphology/pos_twins.tsv (scripts/pos_twins.py: for each word form
            read in more than one part of speech, how many times its tokens are tagged in each
            of fourteen part-of-speech classes).

Shipped as: crates/akana-core/src/parser/light_verbs.txt, compiled into the library.
            DERIVED FROM CC BY-SA DATA: it is distributed under CC BY-SA 4.0.
Changes:    no text is shipped. The list holds the 31 verb roots that a bare noun right before
            them is more often a compound with than their object or subject, counted in the
            train splits (scripts/parser_ud_eval.py --light-verbs).

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3. Turkish WikiNER (Turkish NLP Suite)
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Source:     https://huggingface.co/datasets/turkish-nlp-suite/turkish-wikiNER, revision
            99df1dd7f5a01d39cd5903e51e361d708cb2a5a6: the train and validation splits (the test
            split is used for evaluation only). Wikipedia sentences sampled from the Kuzgunlar
            NER dataset and annotated again by Co-one.
Authors:    Duygu Altinok (Altinok 2023, "A Diverse Set of Freely Available Linguistic Resources
            for Turkish", Proceedings of the 61st Annual Meeting of the Association for
            Computational Linguistics (Volume 1: Long Papers), 13739-13750,
            https://aclanthology.org/2023.acl-long.768).
Licence:    Creative Commons Attribution-ShareAlike 4.0 International,
            https://creativecommons.org/licenses/by-sa/4.0/legalcode

Shipped as: crates/akana-core/src/ner/model.tsv.gz, compiled into the library.
            DERIVED FROM CC BY-SA DATA: it is distributed under CC BY-SA 4.0.
Changes:    no sentence is shipped. The file holds the weights of the named-entity tagger
            (crates/akana-core/src/ner/model.rs, trained by its ignored test train_ner_model on
            what scripts/prepare_wikiner.py writes): a weight per tag for each feature seen more
            than once in training (a word, its first or last letters, its shape, a word next to
            it, ...). WikiNER's PERSON entities are its PER, GPE and LOC its LOC, ORG its ORG;
            the other types are left out.

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4. Common Voice Turkish sentences
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Source:     https://github.com/common-voice/common-voice, commit
            b12cde653757295103c5948c1cd601b166e1b905, server/data/tr/sentence-collector.txt
            (the Turkish sentence collector).
Licence:    CC0 1.0 Universal, public domain dedication (sentence text under server/data, per the
            repository's README.md).

Tests only: crates/akana-core/tests/data/speech/tts_v1_golden.jsonl and tts_v2_golden.jsonl,
            60 of the sentences with Akana's own phonemiser output. Nothing is shipped.

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5. Sources approved for use, from which nothing ships yet
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- Google Research turkish-morphology lexicon (Apache License 2.0), commit 83d4b967.
- TRmorph lexicon by Çağrı Çöltekin (MIT License, copyright (c) 2011-2015 Çağrı Çöltekin),
  commit fbceb113.
- Universal Dependencies Turkish IMST (CC BY-NC-SA 3.0), release r2.18: evaluation only;
  nothing akana ships is derived from it, nor from any UD test split.
- Turkish Wiktionary, as extracted by kaikki.org (Wiktionary content: CC BY-SA 4.0 and GFDL):
  an optional add-on dictionary, distributed apart from the core library if ever built.

When one of these contributes to a shipped file, its entry moves to the list above with the
file, the changes and the licence text (the MIT text for TRmorph).

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Apache License 2.0
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                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

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