Triple

T1235935
Position Surface form Disambiguated ID Type / Status
Subject Complutense University of Madrid E26547 entity
Predicate shortName P43 FINISHED
Object UCM
UCM is the commonly used abbreviation for the Complutense University of Madrid, one of Spain’s largest and most prestigious public universities.
 E140883 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: UCM | Statement: [Complutense University of Madrid, shortName, UCM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UCM
Context triple: [Complutense University of Madrid, shortName, UCM]
  • A. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • B. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • C. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • D. UM
    UM is a public research university in Winnipeg, Canada, known as the University of Manitoba.
  • E. UCH
    UCH is a leading public research university in Santiago, Chile, renowned for its academic excellence and significant influence on the country’s intellectual and cultural life.
  • 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: UCM
Triple: [Complutense University of Madrid, shortName, UCM]
Generated description
UCM is the commonly used abbreviation for the Complutense University of Madrid, one of Spain’s largest and most prestigious public universities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UCM
Target entity description: UCM is the commonly used abbreviation for the Complutense University of Madrid, one of Spain’s largest and most prestigious public universities.
  • A. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • B. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • C. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • D. UM
    UM is a public research university in Winnipeg, Canada, known as the University of Manitoba.
  • E. UCH
    UCH is a leading public research university in Santiago, Chile, renowned for its academic excellence and significant influence on the country’s intellectual and cultural life.
  • 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf17e0bc8190a066561e6b629fc0 completed March 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8a18b0f48190adb5b2c1e2a1019a completed March 7, 2026, 8:27 p.m.
NEDg Description generation batch_69ac8aa863a08190b21071a4ed2e74b9 completed March 7, 2026, 8:29 p.m.
NED2 Entity disambiguation (via description) batch_69ac8b72cb6c8190984bd3d4b0d54262 completed March 7, 2026, 8:32 p.m.
Created at: March 1, 2026, 7:47 p.m.