Triple

T4349767
Position Surface form Disambiguated ID Type / Status
Subject Havant railway station E97993 entity
Predicate hasStationCode P1289 FINISHED
Object HAV E24064 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: HAV | Statement: [Havant railway station, hasStationCode, HAV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HAV
Context triple: [Havant railway station, hasStationCode, HAV]
  • A. HAV chosen
    HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. HA
    HA is the IATA airline designator for Hawaiian Airlines, the largest and longest-serving commercial airline based in Hawaii.
  • C. HAF
    HAF is the commonly used abbreviation for the Hellenic Air Force, the air warfare branch of Greece’s armed forces.
  • D. HV
    HV is the IATA airline designator used by Transavia, a Dutch low-cost carrier operating scheduled and charter flights across Europe and surrounding regions.
  • E. HAD
    HAD is the commonly used abbreviation for the Historical Astronomy Division, a group focused on the study and promotion of the history of astronomy.
  • 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_69b3454965f881908c41190bb22f0e4b completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351a840248190b88c8a7be9158d25 completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbad2f908190b5ee53bc7f2294c9 completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:15 p.m.