Triple

T21472324
Position Surface form Disambiguated ID Type / Status
Subject Ópera metro station E529761 entity
Predicate hasStationCode P1289 FINISHED
Object OPR
OPR is the station code used to identify the Ópera metro station in the Madrid Metro system.
 E1486353 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: OPR | Statement: [Ópera metro station, hasStationCode, OPR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OPR
Context triple: [Ópera metro station, hasStationCode, OPR]
  • A. OPR
    OPR is the post-nominal abbreviation used by recipients of the Polish state order known as the Order of Polonia Restituta.
  • B. OPR
    OPR is a dark, industrial-tinged electronic track by French techno producer Gesaffelstein, recognized as one of his signature works.
  • C. OPR
    OPR is the vehicle registration code used on license plates for the Ostprignitz-Ruppin district in the German state of Brandenburg.
  • D. O.P.
    O.P. is a common abbreviation that can stand for various phrases such as “original poster,” “original post,” or “out of print,” depending on the context in which it is used.
  • E. O.P.
    O.P. is the post-nominal abbreviation for the Order of Preachers, commonly known as the Dominican religious order in the Catholic Church.
  • 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: OPR
Triple: [Ópera metro station, hasStationCode, OPR]
Generated description
OPR is the station code used to identify the Ópera metro station in the Madrid Metro system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OPR
Target entity description: OPR is the station code used to identify the Ópera metro station in the Madrid Metro system.
  • A. OPR
    OPR is the post-nominal abbreviation used by recipients of the Polish state order known as the Order of Polonia Restituta.
  • B. OPR
    OPR is a dark, industrial-tinged electronic track by French techno producer Gesaffelstein, recognized as one of his signature works.
  • C. OPR
    OPR is the vehicle registration code used on license plates for the Ostprignitz-Ruppin district in the German state of Brandenburg.
  • D. O.P.
    O.P. is a common abbreviation that can stand for various phrases such as “original poster,” “original post,” or “out of print,” depending on the context in which it is used.
  • E. O.P.
    O.P. is the post-nominal abbreviation for the Order of Preachers, commonly known as the Dominican religious order in the Catholic Church.
  • 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_69e0c459acb481909bb6ee452a0045c7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea14756081908c615590c68904d5 completed April 23, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09cff96dbc8190adae0f91749530e4 completed May 17, 2026, 2:26 p.m.
NEDg Description generation batch_6a09d08ffa3c8190b5ab7e4cbf78719f completed May 17, 2026, 2:28 p.m.
NED2 Entity disambiguation (via description) batch_6a09d18c77e481908a353d443d79b7ca completed May 17, 2026, 2:32 p.m.
Created at: April 16, 2026, 6:19 p.m.