Triple

T7809671
Position Surface form Disambiguated ID Type / Status
Subject Historic New England E180645 entity
Predicate shortName P43 FINISHED
Object HNE
HNE is the abbreviation for Historic New England, a regional heritage organization dedicated to preserving and interpreting New England’s historic homes, landscapes, and cultural artifacts.
 E694563 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: HNE | Statement: [Historic New England, shortName, HNE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HNE
Context triple: [Historic New England, shortName, HNE]
  • A. HN
    HN is the two-letter ISO 3166-1 alpha-2 country code assigned to Honduras.
  • B. HN
    HN is the vehicle registration code for the city of Heilbronn in the German state of Baden-Württemberg.
  • C. HN
    HN is the station code used to identify RAF Honington, a Royal Air Force station in Suffolk, England.
  • D. HEE
    HEE is the acronym for Health Education England, the national body responsible for overseeing education, training, and workforce development for healthcare staff in England.
  • E. HEL
    HEL is the three-letter IATA airport code for Helsinki Airport, the main international gateway to Finland’s capital region.
  • 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: HNE
Triple: [Historic New England, shortName, HNE]
Generated description
HNE is the abbreviation for Historic New England, a regional heritage organization dedicated to preserving and interpreting New England’s historic homes, landscapes, and cultural artifacts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HNE
Target entity description: HNE is the abbreviation for Historic New England, a regional heritage organization dedicated to preserving and interpreting New England’s historic homes, landscapes, and cultural artifacts.
  • A. HN
    HN is the two-letter ISO 3166-1 alpha-2 country code assigned to Honduras.
  • B. HN
    HN is the station code used to identify RAF Honington, a Royal Air Force station in Suffolk, England.
  • C. HN
    HN is the vehicle registration code for the city of Heilbronn in the German state of Baden-Württemberg.
  • D. HEE
    HEE is the acronym for Health Education England, the national body responsible for overseeing education, training, and workforce development for healthcare staff in England.
  • E. HEL
    HEL is the three-letter IATA airport code for Helsinki Airport, the main international gateway to Finland’s capital region.
  • 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_69ca827f6f148190beca4e245b993506 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69caf78bb4b08190b2b3b51c5a0a033c completed March 30, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb145b93788190a89f26dacbd0b437 completed March 31, 2026, 12:24 a.m.
NEDg Description generation batch_69cb173190a88190b31fd7973bc19d43 completed March 31, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_69cb1a56d25881908b8413b82edf5508 completed March 31, 2026, 12:50 a.m.
Created at: March 30, 2026, 4:37 p.m.