Triple

T17324370
Position Surface form Disambiguated ID Type / Status
Subject GMMN E420647 entity
Predicate hasPassengerTerminal P1297 FINISHED
Object Terminal 1 E9458 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: [GMMN, hasPassengerTerminal, Terminal 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 1
Context triple: [GMMN, hasPassengerTerminal, Terminal 1]
  • A. Terminal 1 chosen
    Terminal 1 is one of the main passenger terminals at Manchester Airport, handling a large share of its international and domestic flights.
  • B. Terminal 1
    Terminal 1 is one of the main passenger terminals at Paris Charles de Gaulle Airport, known for its distinctive circular design and central location within the airport complex.
  • C. 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.
  • D. Terminal 1
    Terminal 1 is a major international passenger terminal at Dubai International Airport that primarily handles flights for numerous international airlines and long-haul routes.
  • E. Terminal 1
    Terminal 1 is a passenger terminal at Trivandrum International Airport in Kerala, India, primarily serving domestic flights and regional operations.
  • 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439d18e3081908ca15baa743abcd8 completed April 19, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a018c4a6630819082998cf754e8361f completed May 11, 2026, 7:59 a.m.
Created at: April 10, 2026, 5:43 a.m.