Triple

T14092821
Position Surface form Disambiguated ID Type / Status
Subject Salahaddin University-Erbil E339177 entity
Predicate locatedIn P40 FINISHED
Object Erbil E67752 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: Erbil | Statement: [Salahaddin University-Erbil, locatedIn, Erbil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erbil
Context triple: [Salahaddin University-Erbil, locatedIn, Erbil]
  • A. Erbil chosen
    Erbil is the capital and largest city of the Kurdistan Region in northern Iraq, known as one of the world’s oldest continuously inhabited urban centers.
  • B. Mosul
    Mosul is a major historic city in northern Iraq, known as a cultural and economic center on the Tigris River.
  • C. Duhok
    Duhok is a city in the Kurdistan Region of Iraq, known as a growing cultural and economic center surrounded by mountains near the Turkish and Syrian borders.
  • D. Kirkuk
    Kirkuk is a historically significant, oil-rich and ethnically diverse city in northern Iraq that has long been a focal point of political and territorial disputes.
  • E. 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.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5ee47f0881908aea8b5231b93f2f completed April 14, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda902c598819083c5373172ed758e completed May 8, 2026, 9:12 a.m.
Created at: April 9, 2026, 10:22 p.m.