Triple

T180797
Position Surface form Disambiguated ID Type / Status
Subject Manchester Airport E3870 entity
Predicate hasTerminal P182 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: [Manchester Airport, hasTerminal, Terminal 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 1
Context triple: [Manchester Airport, hasTerminal, Terminal 1]
  • A. Terminal 1
    Terminal 1 is one of the passenger terminals at Los Angeles International Airport, primarily serving domestic flights for several major U.S. airlines.
  • 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 a passenger terminal at San Francisco International Airport that serves as one of the airport’s main facilities for airline check-in, security, and boarding.
  • D. 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.
  • E. Terminal 1
    Terminal 1 is one of the main passenger terminals at Ronald Reagan Washington National Airport, serving various domestic airline operations and traveler services.
  • 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_69a25497e2f08190a040f8c6e1842643 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a25901a9188190b8f510bec8c8e7f2 completed Feb. 28, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2f0b71080819086362f6036b41162 completed Feb. 28, 2026, 1:42 p.m.
Created at: Feb. 28, 2026, 2:40 a.m.