Triple

T8971104
Position Surface form Disambiguated ID Type / Status
Subject Bournemouth railway station E214267 entity
Predicate stationCode P1289 FINISHED
Object BMH
BMH is the National Rail station code for Bournemouth railway station in Dorset, England.
 E770222 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: BMH | Statement: [Bournemouth railway station, stationCode, BMH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BMH
Context triple: [Bournemouth railway station, stationCode, BMH]
  • A. BM
    BM is the post-nominal abbreviation used to denote recipients of the Bravery Medal, an Australian award for acts of courage.
  • B. BM
    BM is the abbreviated name of Hungary’s Ministry of the Interior, the government body responsible for internal affairs, law enforcement, and public administration.
  • C. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • D. BMM
    BMM (Business Motivation Model) is a standardized framework by the Object Management Group for modeling and analyzing an organization’s business plans, motivations, and governance.
  • E. BdM
    BdM is the central bank of Mexico, responsible for maintaining the country’s monetary stability and issuing its currency.
  • 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: BMH
Triple: [Bournemouth railway station, stationCode, BMH]
Generated description
BMH is the National Rail station code for Bournemouth railway station in Dorset, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BMH
Target entity description: BMH is the National Rail station code for Bournemouth railway station in Dorset, England.
  • A. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • B. BM
    BM is the post-nominal abbreviation used to denote recipients of the Bravery Medal, an Australian award for acts of courage.
  • C. BM
    BM is the abbreviated name of Hungary’s Ministry of the Interior, the government body responsible for internal affairs, law enforcement, and public administration.
  • D. BMM
    BMM (Business Motivation Model) is a standardized framework by the Object Management Group for modeling and analyzing an organization’s business plans, motivations, and governance.
  • E. BdM
    BdM is the central bank of Mexico, responsible for maintaining the country’s monetary stability and issuing its currency.
  • 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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc67672c108190919ae6ca69b6291f completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc9632afc8190a4dc14d33e8757ee completed April 3, 2026, 2:06 p.m.
NEDg Description generation batch_69cfcb178d488190ab8ea897f964c10a completed April 3, 2026, 2:13 p.m.
NED2 Entity disambiguation (via description) batch_69cfcc1bb3248190ac94ed37be2dcde4 completed April 3, 2026, 2:18 p.m.
Created at: March 30, 2026, 7:02 p.m.