Triple

T15715209
Position Surface form Disambiguated ID Type / Status
Subject M. Emmet Walsh E380942 entity
Predicate notableWork P4 FINISHED
Object Airport 77 E829402 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: Airport 77 | Statement: [M. Emmet Walsh, notableWork, Airport 77]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airport 77
Context triple: [M. Emmet Walsh, notableWork, Airport 77]
  • A. Airport ’77 chosen
    Airport ’77 is a 1977 American disaster film in the Airport franchise, centered on a luxury jet that crashes into the ocean and becomes trapped underwater.
  • B. Terminal 2E
    Terminal 2E is a major international passenger terminal at Paris Charles de Gaulle Airport, known for handling many long-haul and Air France flights.
  • C. Flughafen
    Flughafen is the Nuremberg U-Bahn station that serves Nuremberg Airport, providing direct metro access between the airport and the city.
  • D. Terminal 7
    Terminal 7 is one of the passenger terminals at John F. Kennedy International Airport in New York City, historically serving several international airlines.
  • E. Terminal 7
    Terminal 7 is one of the passenger terminals at Los Angeles International Airport, primarily serving United Airlines and its partner carriers.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f90aea0819082a9e9fe0f7780b0 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff7581302c8190918266f04bcf2231 completed May 9, 2026, 5:57 p.m.
Created at: April 10, 2026, 4:45 a.m.