Triple

T2851703
Position Surface form Disambiguated ID Type / Status
Subject Ricardo Wolf E63105 entity
Predicate placeOfDeath P21 FINISHED
Object Herzliya E60622 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: Herzliya | Statement: [Ricardo Wolf, placeOfDeath, Herzliya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herzliya
Context triple: [Ricardo Wolf, placeOfDeath, Herzliya]
  • A. Herzliya chosen
    Herzliya is a coastal city in central Israel known as a high-tech and academic hub, home to major technology companies and institutions.
  • B. Ramat Gan
    Ramat Gan is a city in the Tel Aviv District of Israel, known for its diamond exchange district, business centers, and large urban park.
  • C. Petah Tikva
    Petah Tikva is a major city in central Israel, known as one of the country’s oldest modern Jewish settlements and a significant industrial and commercial hub in the Tel Aviv metropolitan area.
  • D. Kiryat Ono
    Kiryat Ono is a small suburban city in central Israel, located in the Tel Aviv metropolitan area.
  • E. Rehovot
    Rehovot is a city in central Israel known for its scientific and agricultural research institutions, including the Weizmann Institute of Science.
  • 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_69ab4c407c408190857d25e027155ce9 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf5ca2648190bd32c6ec4b0dd3b6 completed March 7, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108ca2c108190b0a341cf039a82bf completed March 11, 2026, 6:16 a.m.
Created at: March 6, 2026, 10:02 p.m.