Triple

T1707088
Position Surface form Disambiguated ID Type / Status
Subject Unidad Militar de Emergencias E36895 entity
Predicate shortName P43 FINISHED
Object UME
UME is Spain’s specialized military emergency unit responsible for rapid response to natural disasters, major accidents, and other civil emergencies.
 E192345 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: UME | Statement: [Unidad Militar de Emergencias, shortName, UME]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UME
Context triple: [Unidad Militar de Emergencias, shortName, UME]
  • A. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • B. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • C. UM
    UM is a public research university in Winnipeg, Canada, known as the University of Manitoba.
  • D. Uni
    Uni is an Etruscan goddess, broadly equivalent to the Roman Juno and Greek Hera, associated with marriage, fertility, and protection of the state.
  • E. UA
    UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
  • 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: UME
Triple: [Unidad Militar de Emergencias, shortName, UME]
Generated description
UME is Spain’s specialized military emergency unit responsible for rapid response to natural disasters, major accidents, and other civil emergencies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UME
Target entity description: UME is Spain’s specialized military emergency unit responsible for rapid response to natural disasters, major accidents, and other civil emergencies.
  • A. UM
    UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
  • B. UM
    UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
  • C. UM
    UM is a public research university in Winnipeg, Canada, known as the University of Manitoba.
  • D. Uni
    Uni is an Etruscan goddess, broadly equivalent to the Roman Juno and Greek Hera, associated with marriage, fertility, and protection of the state.
  • E. UA
    UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
  • 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_69a88617439c819094ffb5d16a0f6307 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62f6fc9c8190b61cc9872cc2adc0 completed March 6, 2026, 5:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8ad849648190b2bb0e2a50cd6c75 completed March 8, 2026, 2:42 p.m.
NEDg Description generation batch_69ad957778a0819080f7fee35f5d8ed5 completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97aa308c81909f245a2133fc471b completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:30 p.m.