Triple

T14663154
Position Surface form Disambiguated ID Type / Status
Subject Abadan E344295 entity
Predicate administrativeDivision P747 FINISHED
Object Abadan County E1112715 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: Abadan County | Statement: [Abadan, administrativeDivision, Abadan County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abadan County
Context triple: [Abadan, administrativeDivision, Abadan County]
  • A. Abadan County chosen
    Abadan County is an administrative division in Khuzestan Province in southwestern Iran, centered around the oil-rich city of Abadan.
  • B. Marand County
    Marand County is an administrative region in East Azerbaijan Province in northwestern Iran, centered around the city of Marand.
  • C. Pishva County
    Pishva County is an administrative subdivision in northern Iran known for its location within Tehran Province and its proximity to the capital city.
  • D. Firuzkuh County
    Firuzkuh County is an administrative subdivision in northeastern Tehran Province, Iran, known for its mountainous terrain, cold climate, and natural attractions.
  • E. Pakdasht County
    Pakdasht County is an administrative subdivision in Iran located southeast of Tehran, known for its agricultural activities and proximity to the capital.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54ae5ac81908cc69891f280e5f7 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde175db5881908f88d2b3fd72bb52 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:27 a.m.