Triple

T2996108
Position Surface form Disambiguated ID Type / Status
Subject RAF Honington E81069 entity
Predicate stationCode P1289 FINISHED
Object HN
HN is the station code used to identify RAF Honington, a Royal Air Force station in Suffolk, England.
E315792 NE FINISHED

How this triple was built (4 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: HN | Statement: [RAF Honington, stationCode, HN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HN
Context triple: [RAF Honington, stationCode, HN]
  • A. HN
    HN is the two-letter ISO 3166-1 alpha-2 country code assigned to Honduras.
  • B. NH
    NH is the official two-letter United States Postal Service abbreviation for the state of New Hampshire.
  • C. NH
    NH is the two-letter IATA airline designator assigned to All Nippon Airways, Japan’s largest airline.
  • D. HB
    HB is the second-generation Holden Torana small family car series produced in the late 1960s, known for introducing more modern styling and engineering updates over its predecessor.
  • E. HM
    HM is an abbreviation commonly used as a formal title for a reigning queen or king, standing for "Her Majesty" or "His Majesty."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: HN
Triple: [RAF Honington, stationCode, HN]
Generated description
HN is the station code used to identify RAF Honington, a Royal Air Force station in Suffolk, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: HN
Target entity description: HN is the station code used to identify RAF Honington, a Royal Air Force station in Suffolk, England.
  • A. HN
    HN is the two-letter ISO 3166-1 alpha-2 country code assigned to Honduras.
  • B. NH
    NH is the official two-letter United States Postal Service abbreviation for the state of New Hampshire.
  • C. NH
    NH is the two-letter IATA airline designator assigned to All Nippon Airways, Japan’s largest airline.
  • D. HB
    HB is the second-generation Holden Torana small family car series produced in the late 1960s, known for introducing more modern styling and engineering updates over its predecessor.
  • E. HM
    HM is a prefix used for classes and APIs in Apple's HomeKit framework, which enables communication and control of smart home accessories on iOS and other Apple platforms.
  • F. None of above. chosen

Provenance (5 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_69ad8b187fc8819085914d3c9ea3142d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99f481688190ae8cd1e057f9dfc7 completed March 8, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b10908cfe48190bf244d5a3dbc958b completed March 11, 2026, 6:17 a.m.
NEDg Description generation batch_69b10ab5e3488190b2d8c98dd296cbe5 completed March 11, 2026, 6:24 a.m.
NED2 Entity disambiguation (via description) batch_69b10b1664f081909b521ee8dd5954f9 completed March 11, 2026, 6:26 a.m.
Created at: March 8, 2026, 2:59 p.m.