Triple

T12526892
Position Surface form Disambiguated ID Type / Status
Subject OPDB E299462 entity
Predicate identifies P310 FINISHED
Object Dalbandin Airport E299461 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: Dalbandin Airport | Statement: [OPDB, identifies, Dalbandin Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dalbandin Airport
Context triple: [OPDB, identifies, Dalbandin Airport]
  • A. Dalbandin Airport chosen
    Dalbandin Airport is a small domestic airport serving the town of Dalbandin in Balochistan, Pakistan, providing regional air connectivity.
  • B. Shah Makhdum Airport
    Shah Makhdum Airport is a regional domestic airport serving the city of Rajshahi in western Bangladesh.
  • C. Chaghcharan Airport
    Chaghcharan Airport is a small regional airport serving the town of Chaghcharan in central Afghanistan, providing vital air connectivity to this remote area.
  • D. Humera Airport
    Humera Airport is a regional airport in northwestern Ethiopia that serves the town of Humera and its surrounding area.
  • E. Sardar Jangal Airport
    Sardar Jangal Airport is the main domestic airport serving the city of Rasht in Iran’s Gilan Province.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545d7e6c819080c3a85c18caa1ae completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ea78dcc819091773d900ad44be6 completed May 2, 2026, 11:54 p.m.
Created at: April 8, 2026, 9:57 p.m.