Triple

T16066573
Position Surface form Disambiguated ID Type / Status
Subject Omer E389746 entity
Predicate hasNotableBearerExample P458 FINISHED
Object Omer Bar-Lev E1145977 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: Omer Bar-Lev | Statement: [Omer, hasNotableBearerExample, Omer Bar-Lev]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Omer Bar-Lev
Context triple: [Omer, hasNotableBearerExample, Omer Bar-Lev]
  • A. Omer Bar-Lev chosen
    Omer Bar-Lev is an Israeli politician and former military officer who has served as a member of the Knesset and held senior roles in Israel’s security and public safety establishment.
  • B. Haim Bar-Lev
    Haim Bar-Lev was an Israeli military leader and politician, best known as IDF Chief of Staff and for the Bar-Lev Line defensive system along the Suez Canal.
  • C. Oren Uziel
    Oren Uziel is an American screenwriter and filmmaker known for genre-blending projects such as The Cloverfield Paradox and 22 Jump Street.
  • D. Moshe Edery
    Moshe Edery is an Israeli film producer and distributor known for his significant role in the Israeli cinema industry.
  • E. Uri Tadmor
    Uri Tadmor is a linguist known for his research on Austronesian languages, particularly the Lamaholot language of eastern Indonesia.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837ca628819081dfc439fe322d58 completed April 17, 2026, 12:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a000ec4d9808190a3d1bfc8f3d73168 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 4:57 a.m.