Triple

T7542648
Position Surface form Disambiguated ID Type / Status
Subject Jorhat Airport E178316 entity
Predicate alsoKnownAs P39 FINISHED
Object Rowriah Airport E188426 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: Rowriah Airport | Statement: [Jorhat Airport, alsoKnownAs, Rowriah Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rowriah Airport
Context triple: [Jorhat Airport, alsoKnownAs, Rowriah Airport]
  • A. Rowriah Airport chosen
    Rowriah Airport is a domestic airport serving the city of Jorhat in the Indian state of Assam.
  • B. Totegegie Airport
    Totegegie Airport is the main air gateway serving the remote Gambier Islands in French Polynesia, providing vital connections to other parts of the territory.
  • C. Starfish Airport
    Starfish Airport is a major international aviation hub in Beijing, China, renowned for its distinctive starfish-shaped terminal designed by architect Zaha Hadid.
  • D. Mwanza Airport
    Mwanza Airport is a regional airport in Mwanza, Tanzania, serving as a key hub for domestic flights and connections around Lake Victoria.
  • E. Katherine Airport
    Katherine Airport is a regional airport in the Northern Territory of Australia that serves the town of Katherine and its surrounding areas.
  • 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_69c69f2be3888190a6667a27f8f195e9 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8762b048190a0b262f9cb3fe1b0 completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856b93188819080c769a2a1b122f4 completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:48 p.m.