Triple

T15320305
Position Surface form Disambiguated ID Type / Status
Subject James Tisch E366269 entity
Predicate familyName P18 FINISHED
Object Tisch E69329 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: Tisch | Statement: [James Tisch, familyName, Tisch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tisch
Context triple: [James Tisch, familyName, Tisch]
  • A. Tisch chosen
    Tisch is a surname most prominently associated with the American Tisch family, known for their influence in business, philanthropy, and the entertainment industry.
  • B. Tahta
    Tahta is a city in Upper Egypt located within the Sohag Governorate, known as a regional center for agriculture and local trade along the Nile.
  • C. The Table
    "The Table" is the English name of Surah Al-Ma'idah, a chapter of the Qur'an that addresses themes of lawful and unlawful food, covenants, and adherence to divine law.
  • D. The Table
    The Table is a distinctive flat-topped volcanic mesa located in Garibaldi Provincial Park in British Columbia, Canada.
  • E. Tábua
    Tábua is a municipality in central Portugal known for its rural landscapes, traditional villages, and location between the Mondego and Alva rivers.
  • 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03dd460288190b5c41f0a0aeee949 completed April 16, 2026, 1:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8a9085881909904152c32b0fed1 completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:16 a.m.