Triple

T6862413
Position Surface form Disambiguated ID Type / Status
Subject MEL E158312 entity
Predicate hasTerminal P182 FINISHED
Object Terminal 1 E170163 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: Terminal 1 | Statement: [MEL, hasTerminal, Terminal 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 1
Context triple: [MEL, hasTerminal, Terminal 1]
  • A. Terminal 1
    Terminal 1 is the main passenger terminal at El Dorado International Airport in Bogotá, Colombia, handling the majority of the airport’s domestic and international flights.
  • B. Terminal 1
    Terminal 1 is one of the main passenger terminals at Nice Côte d’Azur Airport, serving a variety of international and domestic flights on the French Riviera.
  • C. Terminal 1 chosen
    Terminal 1 is a major domestic passenger terminal at Melbourne Airport primarily serving Australian airlines and internal flights.
  • D. Terminal 1
    Terminal 1 is a main passenger terminal at Birmingham Airport in the United Kingdom, handling check-in, security, departures, and arrivals for various domestic and international flights.
  • E. Terminal 1
    Terminal 1 is a passenger terminal at Chaudhary Charan Singh International Airport in Lucknow, India, serving as one of the airport’s main facilities for handling air travelers.
  • 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_69c68830cdbc8190a8301c7a9d9f651a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d887d6648190a0c2d1cb1b284bfe completed March 27, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72fed3e788190b2b68fc93173f73e completed March 28, 2026, 1:33 a.m.
Created at: March 27, 2026, 2:21 p.m.