Triple

T6211100
Position Surface form Disambiguated ID Type / Status
Subject CDG Terminal 2 E138870 entity
Predicate hasPart P35 FINISHED
Object Terminal 2B E67384 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: [CDG Terminal 2, hasPart, Terminal 2B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 2B
Context triple: [CDG Terminal 2, hasPart, Terminal 2B]
  • A. Terminal 2B chosen
    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 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.
  • D. Terminal 1B
    Terminal 1B is a passenger terminal at Jomo Kenyatta International Airport in Nairobi, Kenya, serving scheduled commercial flights and related airport services.
  • E. Terminal 2F
    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.
  • 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_69c008ada364819096c9e92c74d639b5 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062896f3881909f264bb45badc5d0 completed March 22, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20da55e3c81909a61471b38e88894 completed March 24, 2026, 4:05 a.m.
Created at: March 22, 2026, 4:21 p.m.