Triple

T3263009
Position Surface form Disambiguated ID Type / Status
Subject Terminal 2E E68455 entity
Predicate connectedTo P37 FINISHED
Object Terminal 2F E68666 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 2F | Statement: [Terminal 2E, connectedTo, Terminal 2F]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 2F
Context triple: [Terminal 2E, connectedTo, Terminal 2F]
  • A. Terminal 2F chosen
    Terminal 2F is one of the passenger terminals at Paris Charles de Gaulle Airport, primarily serving international flights with dedicated check-in, security, and boarding facilities.
  • B. 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.
  • C. Terminal 2A
    Terminal 2A 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.
  • D. 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.
  • E. Terminal 2 station
    Terminal 2 station is a metro stop on Beijing’s Capital Airport Express line serving Terminal 2 of Beijing Capital International Airport.
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafa908e881908cbb2ad137819ffb completed March 8, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e83a7a508190afd5342c79f3da9d completed March 12, 2026, 4:22 p.m.
Created at: March 8, 2026, 3:09 p.m.