Triple

T9195184
Position Surface form Disambiguated ID Type / Status
Subject Bellmore station E220686 entity
Predicate code P1537 FINISHED
Object BMR
BMR is the station code for Bellmore station on the Long Island Rail Road in New York.
 E783629 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: BMR | Statement: [Bellmore station, code, BMR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BMR
Context triple: [Bellmore station, code, BMR]
  • A. BMR
    BMR is the National Rail station code for Barlow Moor Road railway station in the United Kingdom.
  • B. RMR
    The RMR is a Canadian Army Primary Reserve infantry regiment based in Westmount, Quebec, with a distinguished history of service in both World Wars and subsequent conflicts.
  • C. BM
    BM is the post-nominal abbreviation used to denote recipients of the Bravery Medal, an Australian award for acts of courage.
  • D. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • E. 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.
  • 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: BMR
Triple: [Bellmore station, code, BMR]
Generated description
BMR is the station code for Bellmore station on the Long Island Rail Road in New York.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BMR
Target entity description: BMR is the station code for Bellmore station on the Long Island Rail Road in New York.
  • A. BMR
    BMR is the National Rail station code for Barlow Moor Road railway station in the United Kingdom.
  • B. RMR
    The RMR is a Canadian Army Primary Reserve infantry regiment based in Westmount, Quebec, with a distinguished history of service in both World Wars and subsequent conflicts.
  • C. BM
    BM is the post-nominal abbreviation used to denote recipients of the Bravery Medal, an Australian award for acts of courage.
  • D. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • E. 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.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd87c3a3c8190b60f19873ef6e1f8 completed April 1, 2026, 8:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c36d7208190a593923bad3d18e7 completed April 4, 2026, 12:32 a.m.
NEDg Description generation batch_69d05cb45280819096747ff8f7d5c2a0 completed April 4, 2026, 12:35 a.m.
NED2 Entity disambiguation (via description) batch_69d05d5d29f4819081c28b24cb2058b0 completed April 4, 2026, 12:37 a.m.
Created at: March 30, 2026, 7:25 p.m.