Triple

T2603846
Position Surface form Disambiguated ID Type / Status
Subject LS E58608 entity
Predicate airlineSecondaryBaseAirportCode P40597 FINISHED
Object BFS E97800 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: BFS | Statement: [LS, airlineSecondaryBaseAirportCode, BFS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BFS
Context triple: [LS, airlineSecondaryBaseAirportCode, BFS]
  • A. BFS chosen
    BFS is the three-letter IATA airport code assigned to Belfast International Airport in Northern Ireland.
  • B. DFS
    DFS is the commonly used abbreviation for the New York State Department of Financial Services, the state agency that regulates financial services and products in New York.
  • C. DFS
    DFS is the stock ticker symbol for Discover Financial Services, a major U.S. financial services company best known for its Discover credit card network and related banking products.
  • D. EBFS
    EBFS is the ICAO airport code for Florennes Air Base, a military airfield in Belgium.
  • E. Dijkstra
    Dijkstra is a renowned Dutch computer scientist best known for his pioneering work in algorithms, including Dijkstra's shortest path algorithm, and for his influential contributions to programming methodology and software engineering.
  • 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_69ab4ac3523881909679750c9f8c2dec completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abdd1ca0248190aa15f80b2798524e completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83d6daa4819087ee111e648ce71d completed March 10, 2026, 2:37 a.m.
Created at: March 6, 2026, 9:49 p.m.