Triple

T18167857
Position Surface form Disambiguated ID Type / Status
Subject Bisacquino E434939 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object PA NE NERFINISHED

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: PA | Statement: [Bisacquino, vehicleRegistrationCode, PA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PA
Context triple: [Bisacquino, vehicleRegistrationCode, PA]
  • A. PA
    PA is the postcode area in western Scotland that covers Paisley and parts of the surrounding Greater Glasgow region.
  • B. PA
    PA is the standard abbreviation for the Pakistan Army, the principal land warfare branch of Pakistan's armed forces.
  • C. PA chosen
    PA is the provincial code for the Metropolitan City of Palermo in the Sicily region of Italy.
  • D. PA
    PA is the official abbreviation for the Philippine Army, the main ground warfare branch of the Armed Forces of the Philippines.
  • E. PA
    PA is the former IATA airline designator for Pan American World Airways, the pioneering and once-dominant U.S. international airline.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90b7a188190b3fc7b8d4a6cd20a completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4df52f8b08190ab2c4d76b510cd28 completed April 19, 2026, 1:57 p.m.
Created at: April 10, 2026, 10:30 a.m.