Triple

T215594
Position Surface form Disambiguated ID Type / Status
Subject Historic Environment Scotland E4813 entity
Predicate shortName P43 FINISHED
Object HES
HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
 E27570 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: HES | Statement: [Historic Environment Scotland, shortName, HES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HES
Context triple: [Historic Environment Scotland, shortName, HES]
  • A. HAV
    HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. HRS
    HRS is an abbreviation commonly used for the Historical Records Survey, a New Deal-era program that documented and preserved historical public records in the United States.
  • C. SHASS
    SHASS is the abbreviated name commonly used for the School of Humanities, Arts, and Social Sciences at academic institutions.
  • D. HM
    HM is an abbreviation commonly used as a formal title for a reigning queen or king, standing for "Her Majesty" or "His Majesty."
  • E. HUP
    HUP is a major academic medical center in Philadelphia that serves as the flagship teaching hospital of the University of Pennsylvania's health system.
  • 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: HES
Triple: [Historic Environment Scotland, shortName, HES]
Generated description
HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HES
Target entity description: HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
  • A. HAV
    HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. HRS
    HRS is an abbreviation commonly used for the Historical Records Survey, a New Deal-era program that documented and preserved historical public records in the United States.
  • C. SHASS
    SHASS is the abbreviated name commonly used for the School of Humanities, Arts, and Social Sciences at academic institutions.
  • D. HM
    HM is an abbreviation commonly used as a formal title for a reigning queen or king, standing for "Her Majesty" or "His Majesty."
  • E. HUP
    HUP is a major academic medical center in Philadelphia that serves as the flagship teaching hospital of the University of Pennsylvania's health system.
  • 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_69a2575cb1dc8190a01ad332426dc339 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c4ca0c8819093f63c6371e2d140 completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a33e3f66888190a05ddcb0af4d3c5f completed Feb. 28, 2026, 7:13 p.m.
NEDg Description generation batch_69a33ee88af08190bfe81fba01856829 completed Feb. 28, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_69a34295afa88190aae0d75a337967e3 completed Feb. 28, 2026, 7:31 p.m.
Created at: Feb. 28, 2026, 2:52 a.m.