Triple

T148675
Position Surface form Disambiguated ID Type / Status
Subject HM Treasury E3383 entity
Predicate hasAbbreviation P43 FINISHED
Object HMT
HMT is the commonly used abbreviation for HM Treasury, the United Kingdom government department responsible for economic and financial policy.
 E17854 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: HMT | Statement: [HM Treasury, hasAbbreviation, HMT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HMT
Context triple: [HM Treasury, hasAbbreviation, HMT]
  • A. AMTK
    AMTK is the reporting mark used by Amtrak, the United States’ national passenger railroad service, to identify its locomotives and rolling stock.
  • B. Porter
    Porter is a transit station in Cambridge, Massachusetts that serves both MBTA commuter rail and Red Line subway services.
  • C. EMD
    EMD is the commonly used abbreviation for the Engineering Management Division, a professional group focused on the practice and advancement of engineering management.
  • D. Leatherhead
    Leatherhead is a historic market town in the county of Surrey in South East England, situated on the River Mole and serving as a local commercial and commuter hub.
  • E. NMTI
    NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
  • 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: HMT
Triple: [HM Treasury, hasAbbreviation, HMT]
Generated description
HMT is the commonly used abbreviation for HM Treasury, the United Kingdom government department responsible for economic and financial policy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HMT
Target entity description: HMT is the commonly used abbreviation for HM Treasury, the United Kingdom government department responsible for economic and financial policy.
  • A. AMTK
    AMTK is the reporting mark used by Amtrak, the United States’ national passenger railroad service, to identify its locomotives and rolling stock.
  • B. Porter
    Porter is a transit station in Cambridge, Massachusetts that serves both MBTA commuter rail and Red Line subway services.
  • C. EMD
    EMD is the commonly used abbreviation for the Engineering Management Division, a professional group focused on the practice and advancement of engineering management.
  • D. Leatherhead
    Leatherhead is a historic market town in the county of Surrey in South East England, situated on the River Mole and serving as a local commercial and commuter hub.
  • E. NMTI
    NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
  • 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_69a252868de4819080e21c9938bfe8b6 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a257ecb6f48190992c4c8ca908a81c completed Feb. 28, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2c52df3b48190960c53fd872ff897 completed Feb. 28, 2026, 10:36 a.m.
NEDg Description generation batch_69a2c5a7925481909fa398453451a126 completed Feb. 28, 2026, 10:38 a.m.
NED2 Entity disambiguation (via description) batch_69a2c60ae5108190b735939eac69e11a completed Feb. 28, 2026, 10:40 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.