Triple

T10591027
Position Surface form Disambiguated ID Type / Status
Subject Ghat District E249986 entity
Predicate hasTransport P1298 FINISHED
Object Ghat Airport E249988 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: Ghat Airport | Statement: [Ghat District, hasTransport, Ghat Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ghat Airport
Context triple: [Ghat District, hasTransport, Ghat Airport]
  • A. Ghat Airport chosen
    Ghat Airport is a small regional airport serving the town of Ghat in southwestern Libya, primarily handling domestic flights.
  • B. Kheria Airport
    Kheria Airport is a domestic and military airfield serving the city of Agra in Uttar Pradesh, India, located near the Taj Mahal and operated jointly by the Indian Air Force and civil aviation authorities.
  • C. Bilasa Devi Kevat Airport
    Bilasa Devi Kevat Airport is a regional domestic airport serving the city of Bilaspur in the Indian state of Chhattisgarh.
  • D. Lata Airport
    Lata Airport is a small regional airfield serving the town of Lata in the Solomon Islands, providing vital air connectivity to this remote area.
  • E. Akola Airport
    Akola Airport is a domestic airport serving the city of Akola in Maharashtra, India, primarily handling regional air traffic.
  • 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5277b66448190b668c47fe6af4f3d completed April 7, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b99b3248190b5eac0e99cb73d4b completed April 10, 2026, 7:12 p.m.
Created at: April 6, 2026, 12:40 p.m.