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Record W3121601712 · doi:10.7146/hn.v5i2.142742

Interfacing the Hebrew Bible: past, present and future applications for the BHSA

2019· article· en· W3121601712 on OpenAlexaff
Nicolai Winther-Nielsen

Bibliographic record

VenueHIPHIL Novum · 2019
Typearticle
Languageen
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsLearning Partnership
Fundersnot available
KeywordsLinguisticsHebrewComputer scienceHebrew BibleSyntaxBiblical languagesGrammarSemantics (computer science)Interface (matter)Interpretation (philosophy)Artificial intelligenceBiblical studiesLiteraturePhilosophyArtProgramming language

Abstract

fetched live from OpenAlex

The open and constantly evolving BHSA database text of the Hebrew Bible (Biblia Hebraica Stuttgartensia Amstelodamensis) from the Eep Talstra Centre for Bible and Computer has amazing potential for past, present and future projects in Biblical Hebrew linguistics, language learning and interpretation. The BHSA was used 2004-2009 in the Role Lexical Module http://lex.qwirx.com/lex/clause.jsp in order to provide an interface for bidirectional mapping between morpho-syntax and semantics for linguists working within the Role and Reference Grammar model. Since then the BHSA har been used for educational purposes in the corpus-driven learning environment Bible Online Learner offering a persuasive interface for enquiry and practice in and with the BHSA text. Based on these applications for linguistic research and persuasive language learning, we now have a better idea of how the next generation of interfaces for the Hebrew Bible should be designed. We may even envision the direction to take for the next 5 years from now. For translation and education, we will need glosses for many languages, scaffolding with interactive archaeological, textual, grammatical and interpretive data, auralreading and much more.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.261
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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