Triple

T14737388
Position Surface form Disambiguated ID Type / Status
Subject North Khorasan Province E346248 entity
Predicate containsCity P294 FINISHED
Object Bojnord E221030 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: Bojnord | Statement: [North Khorasan Province, containsCity, Bojnord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bojnord
Context triple: [North Khorasan Province, containsCity, Bojnord]
  • A. Bojnord chosen
    Bojnord is a city in northeastern Iran that serves as the capital of North Khorasan Province.
  • B. Tjeldsund
    Tjeldsund is a coastal municipality in northern Norway known for its location around the Tjeldsundet strait and its mix of island and mainland landscapes.
  • C. Farsund
    Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
  • D. Berlevåg
    Berlevåg is a small coastal town and municipality in Troms og Finnmark county in northern Norway, known for its fishing industry and exposed location on the Barents Sea.
  • E. Grimstad
    Grimstad is a coastal town and municipality in southern Norway known for its maritime heritage, charming wooden houses, and role as a summer tourist destination.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec73264848190be23c5f0260cbe13 completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24ae3d6c819080c015ebc6bc9af0 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:29 a.m.