Triple

T20665319
Position Surface form Disambiguated ID Type / Status
Subject Joel Teitelbaum E507869 entity
Predicate name P16 FINISHED
Object Joel Teitelbaum E507869 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: Joel Teitelbaum | Statement: [Joel Teitelbaum, name, Joel Teitelbaum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joel Teitelbaum
Context triple: [Joel Teitelbaum, name, Joel Teitelbaum]
  • A. Joel Teitelbaum chosen
    Joel Teitelbaum was a prominent Hasidic rabbi and founding Satmar Rebbe, known for leading and shaping the Satmar Hasidic community.
  • B. Zalman Ehrlich
    Zalman Ehrlich is a person notable enough to be recognized as a significant bearer of the surname Ehrlich.
  • C. Nahum Gelber
    Nahum Gelber was a Canadian lawyer, philanthropist, and community leader known for his significant contributions to legal education and Jewish cultural and charitable institutions.
  • D. George Nachman
    George Nachman is a software engineer best known as the creator and maintainer of the popular macOS terminal emulator iTerm2.
  • E. Moshe Diamant
    Moshe Diamant is a film producer known for his work on action and science fiction movies, including the 1994 time-travel film "Timecop."
  • 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_69e0b4c059bc81908ea762cd73ea4424 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b5c2c6d48190bbfe505cf7d973f9 completed April 20, 2026, 11:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08cd5fc3e081909087414333b2615e completed May 16, 2026, 8:02 p.m.
Created at: April 16, 2026, 11:44 a.m.