Triple

T16752950
Position Surface form Disambiguated ID Type / Status
Subject Réseau express métropolitain E407129 entity
Predicate abbreviation P43 FINISHED
Object REM
REM is a fully automated light metro network serving the Greater Montreal area in Quebec, Canada.
E1232178 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: REM | Statement: [Réseau express métropolitain, abbreviation, REM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: REM
Context triple: [Réseau express métropolitain, abbreviation, REM]
  • A. RM
    RM is a UK postcode area in east London and parts of Essex, covering districts such as Romford and surrounding suburbs.
  • B. RM
    RM is a South Korean rapper, songwriter, and leader of the globally renowned K-pop group BTS.
  • C. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • D. RE
    RE is the vehicle registration code used for the city of Recklinghausen in Germany.
  • E. RE
    RE is the two-letter ISO 3166-1 alpha-2 country code assigned to the French overseas department and region of Réunion.
  • 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: REM
Triple: [Réseau express métropolitain, abbreviation, REM]
Generated description
REM is a fully automated light metro network serving the Greater Montreal area in Quebec, Canada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: REM
Target entity description: REM is a fully automated light metro network serving the Greater Montreal area in Quebec, Canada.
  • A. RM
    RM is a UK postcode area in east London and parts of Essex, covering districts such as Romford and surrounding suburbs.
  • B. RM
    RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
  • C. RM
    RM is a South Korean rapper, songwriter, and leader of the globally renowned K-pop group BTS.
  • D. RE
    RE is a centrist, pro-European French political party founded by Emmanuel Macron and formerly known as La République En Marche!.
  • E. RE
    RE is the vehicle registration code used for the city of Recklinghausen in Germany.
  • 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3aa282bb08190992c9b61caa7a345 completed April 18, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a52402848190b029cb0be31b4c74 completed May 10, 2026, 3:32 p.m.
NEDg Description generation batch_6a00a5c4e934819088db49d81be154c3 completed May 10, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a00a6b84d288190aeccb06745146b80 completed May 10, 2026, 3:39 p.m.
Created at: April 10, 2026, 5:21 a.m.