Triple

T14862928
Position Surface form Disambiguated ID Type / Status
Subject Hamilton railway station E349542 entity
Predicate hasStationCode P1289 FINISHED
Object HMT
HMT is the station code for Hamilton railway station in Scotland’s national rail network.
 E1123777 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: [Hamilton railway station, hasStationCode, HMT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HMT
Context triple: [Hamilton railway station, hasStationCode, HMT]
  • A. HMT
    HMT is the commonly used abbreviation for HM Treasury, the United Kingdom government department responsible for economic and financial policy.
  • B. HMTM
    HMTM is a renowned German conservatory in Munich specializing in higher education for music and performing arts.
  • C. HMT Leipzig
    HMT Leipzig is a renowned German conservatory in Leipzig specializing in music and theatre education, named after composer Felix Mendelssohn Bartholdy.
  • D. HMHS
    HMHS is the registration prefix used to designate British hospital ships, standing for "His/Her Majesty's Hospital Ship."
  • E. Hanomag
    Hanomag was a German engineering and vehicle manufacturing company best known for producing military half-tracks and civilian tractors in the first half of the 20th century.
  • 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: [Hamilton railway station, hasStationCode, HMT]
Generated description
HMT is the station code for Hamilton railway station in Scotland’s national rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HMT
Target entity description: HMT is the station code for Hamilton railway station in Scotland’s national rail network.
  • A. HMT
    HMT is the commonly used abbreviation for HM Treasury, the United Kingdom government department responsible for economic and financial policy.
  • B. HMTM
    HMTM is a renowned German conservatory in Munich specializing in higher education for music and performing arts.
  • C. HMT Leipzig
    HMT Leipzig is a renowned German conservatory in Leipzig specializing in music and theatre education, named after composer Felix Mendelssohn Bartholdy.
  • D. HMHS
    HMHS is the registration prefix used to designate British hospital ships, standing for "His/Her Majesty's Hospital Ship."
  • E. Hanomag
    Hanomag was a German engineering and vehicle manufacturing company best known for producing military half-tracks and civilian tractors in the first half of the 20th century.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded574d0ec8190a6afed672ba6c2f9 completed April 15, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe650c41b081909cdadbaec472eee3 completed May 8, 2026, 10:34 p.m.
NEDg Description generation batch_69fe66218cb88190b8c86b359abaa14c completed May 8, 2026, 10:39 p.m.
NED2 Entity disambiguation (via description) batch_69fe66de57cc8190935d764d399f56f5 completed May 8, 2026, 10:42 p.m.
Created at: April 10, 2026, 1:54 a.m.