Triple

T631995
Position Surface form Disambiguated ID Type / Status
Subject Islamic world E15944 entity
Predicate hasCulturalCenter P2412 FINISHED
Object Najaf E67251 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: Najaf | Statement: [Islamic world, hasCulturalCenter, Najaf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Najaf
Context triple: [Islamic world, hasCulturalCenter, Najaf]
  • A. Najaf chosen
    Najaf is a major Iraqi city revered as a holy center of Shia Islam and home to the Imam Ali Shrine.
  • B. Tikrit
    Tikrit is a city in northern Iraq best known as the hometown of former president Saddam Hussein and a focal point in recent Iraqi history.
  • C. Basra
    Basra is a historic port city in southern Iraq, strategically located near the Persian Gulf and long significant as a commercial and cultural hub of the region.
  • D. Sulaymaniyah
    Sulaymaniyah is a major city in the Kurdistan Region of Iraq, known as a cultural and economic center with a diverse linguistic landscape.
  • E. Baghdad
    Baghdad is the capital and largest city of Iraq, historically renowned as a major center of the Islamic Golden Age and a key cultural and economic hub of the Arab world.
  • 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_69a580335a5c819096d0c105178c4ad7 completed March 2, 2026, 12:18 p.m.
Created at: March 1, 2026, 7:35 p.m.