Triple

T12076665
Position Surface form Disambiguated ID Type / Status
Subject Habima Theatre building, Tel Aviv E287566 entity
Predicate architect P184 FINISHED
Object Yakov Rechter E57523 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: Yakov Rechter | Statement: [Habima Theatre building, Tel Aviv, architect, Yakov Rechter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yakov Rechter
Context triple: [Habima Theatre building, Tel Aviv, architect, Yakov Rechter]
  • A. Yakov Rechter chosen
    Yakov Rechter was a prominent Israeli architect known for his modernist public buildings and cultural institutions, which helped shape the architectural landscape of Israel in the 20th century.
  • B. Moshe Kuninsky
    Moshe Kuninsky is an Israeli politician who serves as the mayor of the city of Karmiel.
  • C. Lev Shvarts
    Lev Shvarts was a Soviet composer known for his film scores and other orchestral works during the mid-20th century.
  • D. Lazare Meerson
    Lazare Meerson was a renowned Russian-born French art director celebrated for his influential and imaginative set designs in 1930s European cinema.
  • E. Victor Finkelstein
    Victor Finkelstein was a pioneering disability rights activist and theorist who helped shape the social model of disability in the United Kingdom.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9045ceeec81909427cae8972eed26 completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a6b2d788190975275d713c26a4e completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:48 p.m.