Triple

T631978
Position Surface form Disambiguated ID Type / Status
Subject Islamic world E15944 entity
Predicate hasCulturalCenter P2412 FINISHED
Object Jerusalem E6995 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: Jerusalem | Statement: [Islamic world, hasCulturalCenter, Jerusalem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerusalem
Context triple: [Islamic world, hasCulturalCenter, Jerusalem]
  • A. Jerusalem chosen
    Jerusalem is an ancient and historically significant city in the Middle East that serves as a major religious and cultural center for Judaism, Christianity, and Islam.
  • B. West Jerusalem
    West Jerusalem is the predominantly Jewish, modern western sector of Jerusalem that has served as the seat of Israel’s government institutions since 1949.
  • C. Ramla
    Ramla is an Israeli city historically significant as a major religious and communal center for Karaite Jews.
  • D. Tel Aviv
    Tel Aviv is a major Israeli coastal city known for its vibrant nightlife, high-tech industry, and modernist architecture.
  • E. Bethlehem
    Bethlehem is an ancient town in the West Bank historically revered as the birthplace of Jesus and a major center of Christian pilgrimage.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ec2a4c08190bc5c6ce8a10b0967 completed March 1, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a577891a148190ae1364191f7f63bb completed March 2, 2026, 11:42 a.m.
Created at: March 1, 2026, 7:35 p.m.