Triple

T14601185
Position Surface form Disambiguated ID Type / Status
Subject Terminal 2 complex E342707 entity
Predicate hasPart P35 FINISHED
Object Terminal 2B E652885 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 2B | Statement: [Terminal 2 complex, hasPart, Terminal 2B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 2B
Context triple: [Terminal 2 complex, hasPart, Terminal 2B]
  • A. Terminal 2B
    Terminal 2B is one of the passenger terminals at Paris Charles de Gaulle Airport, serving various international and European flights with check-in, boarding, and arrival facilities.
  • B. Terminal 2B
    Terminal 2B is one of the passenger terminals at Budapest Ferenc Liszt International Airport, primarily serving international flights and Schengen-area traffic.
  • C. Terminal 2B
    Terminal 2B is a satellite concourse of Heathrow Airport’s Terminal 2, serving additional aircraft gates and passenger boarding areas.
  • D. Terminal 2B chosen
    Terminal 2B is one of the sub-terminals within Barcelona–El Prat Airport’s Terminal 2 complex, serving as a dedicated passenger area with its own gates and facilities.
  • E. Terminal 2C
    Terminal 2C is one of the passenger terminals at Paris Charles de Gaulle Airport, serving various international and European flights with check-in, boarding, and arrival facilities.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb438748081908020ce04b869866a completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda91a4d7881908f783beb72578067 completed May 8, 2026, 9:12 a.m.
Created at: April 10, 2026, 1:25 a.m.