Triple

T13281456
Position Surface form Disambiguated ID Type / Status
Subject Hagerstown Regional Airport E316330 entity
Predicate FAAcode P420 FINISHED
Object HGR E1030301 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: HGR | Statement: [Hagerstown Regional Airport, FAAcode, HGR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HGR
Context triple: [Hagerstown Regional Airport, FAAcode, HGR]
  • A. HGR chosen
    HGR is the IATA airport code for Hagerstown Regional Airport, a public airport serving Hagerstown, Maryland, and the surrounding region.
  • B. HG
    HG is the postcode area designation covering Harrogate and surrounding parts of North Yorkshire, England.
  • C. HG
    HG is the vehicle registration code used on license plates for the German town of Homburg vor der Höhe and its surrounding district.
  • D. HGS
    HGS is the National Rail station code assigned to Hastings railway station in East Sussex, England.
  • E. GRH
    GRH is a major unproven conjecture in number theory asserting that all nontrivial zeros of a broad class of L-functions lie on a critical line, generalizing the classical Riemann hypothesis.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9904507588190a303686d176ec3e1 completed April 11, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716cfea308190836eb4892e7c5eb4 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:27 p.m.