Triple

T4838813
Position Surface form Disambiguated ID Type / Status
Subject Shneur Zalman of Liadi E108128 entity
Predicate notableWork P4 FINISHED
Object Tanya E142758 NE FINISHED

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: [Shneur Zalman of Liadi, notableWork, Tanya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanya
Context triple: [Shneur Zalman of Liadi, notableWork, 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 a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
  • E. Tania
    Tania is a feminine given name commonly used as a diminutive or variant of names like Tatyana or Tatiana.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd43fbe444819085cb970706ef73f7 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ce4a5108190aede620d5dde1f81 completed March 20, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5cc5861881908ad3838168325a34 completed March 21, 2026, 8:54 a.m.
Created at: March 20, 2026, 1:25 p.m.