Triple

T180834
Position Surface form Disambiguated ID Type / Status
Subject Manchester Airport E3871 entity
Predicate IATA code P2569 FINISHED
Object MAN E3870 NE FINISHED

How this triple was built (3 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: MAN | Statement: [Manchester Airport, IATA code, MAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MAN
Context triple: [Manchester Airport, IATA code, MAN]
  • A. MAN chosen
    MAN is the three-letter IATA airport code for Manchester Airport, a major international airport serving the Greater Manchester area in England.
  • B. Miller
    Miller is a common English and Scottish occupational surname historically given to people who worked in grain mills.
  • C. Mark
    Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
  • D. Levi
    Levi is the surname of Primo Levi, the renowned Italian Jewish chemist and writer best known for his memoirs about surviving the Auschwitz concentration camp.
  • E. Sen
    Sen is a common Indian surname, particularly prevalent among Bengali communities and associated with numerous notable figures in academia, arts, and public life.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: IATA code
Context triple: [Manchester Airport, IATA code, MAN]
  • A. IATAcode
    Indicates the three-letter IATA airport or airline code assigned to the entity.
  • B. hasIATAcode chosen
    Indicates that an entity, typically a transportation facility like an airport, is associated with a specific IATA (International Air Transport Association) code.
  • C. ICAOcode
    Indicates that an entity is identified by a specific four-letter airport or aerodrome code assigned by the International Civil Aviation Organization (ICAO).
  • D. hasInternationalAirport
    Indicates that a place possesses an airport that handles international flights and services cross-border air traffic.
  • E. FAAcode
    Indicates that an entity (such as an airport or facility) is associated with a specific identifying code assigned by the Federal Aviation Administration (FAA).
  • F. None of above.

Provenance (4 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_69a25497e2f08190a040f8c6e1842643 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a25901a9188190b8f510bec8c8e7f2 completed Feb. 28, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2fa7c7a288190bc547d5e7010732b completed Feb. 28, 2026, 2:23 p.m.
PD Predicate disambiguation batch_69a2566ccc288190add5624ede96d82b completed Feb. 28, 2026, 2:43 a.m.
Created at: Feb. 28, 2026, 2:40 a.m.