Triple

T19767778
Position Surface form Disambiguated ID Type / Status
Subject Baal HaTanya E474802 entity
Predicate authorOf P4244 FINISHED
Object Tanya NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tanya | Statement: [Baal HaTanya, authorOf, Tanya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanya
Context triple: [Baal HaTanya, authorOf, Tanya]
  • A. Tanya chosen
    Tanya is the foundational Chabad-Lubavitch Hasidic work by Rabbi Shneur Zalman of Liadi, presenting a systematic approach to Jewish mysticism, psychology, and spiritual self-improvement.
  • B. Tanya
    Tanya is a common diminutive form of the female given name Tatyana, used in various Slavic and English-speaking contexts.
  • C. Tessa
    Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • D. Lila
    Lila is the daughter of French actress Virginie Ledoyen.
  • E. Lila
    Lila is a novel by Marilynne Robinson that continues her acclaimed Gilead series, exploring themes of grace, poverty, and belonging through the life of its enigmatic title character.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8e51a43a08190956bc6df13c91a77 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65358fc3c8190867fea2a2c4e7594 completed April 20, 2026, 4:24 p.m.
Created at: April 10, 2026, 1:48 p.m.