Triple

T14092789
Position Surface form Disambiguated ID Type / Status
Subject Arbela E339176 entity
Predicate hasAlternativeName P39 FINISHED
Object Arbīl 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: Arbīl | Statement: [Arbela, hasAlternativeName, Arbīl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arbīl
Context triple: [Arbela, hasAlternativeName, Arbīl]
  • 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. 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.
  • C. Zakho
    Zakho is a Kurdish-majority town in the Kurdistan Region of Iraq, near the Turkish border, known as a commercial hub and gateway for cross-border trade.
  • D. Mosul
    Mosul is a major historic city in northern Iraq, known as a cultural and economic center on the Tigris River.
  • E. 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.
  • 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_69fd8a9eeff48190b8aa9a601574395a completed May 8, 2026, 7:02 a.m.
Created at: April 9, 2026, 10:22 p.m.