Triple

T10184124
Position Surface form Disambiguated ID Type / Status
Subject Navy Staff of Spain E236864 entity
Predicate abbreviation P43 FINISHED
Object EMA
EMA is the acronym for the Spanish Navy Staff, the central command body responsible for directing and managing Spain’s naval forces.
 E846515 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: EMA | Statement: [Navy Staff of Spain, abbreviation, EMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EMA
Context triple: [Navy Staff of Spain, abbreviation, EMA]
  • A. EMA
    EMA is the three-letter IATA airport code for East Midlands Airport in England, which serves the East Midlands region with domestic and international flights.
  • B. EMA
    EMA is the abbreviated name for the Joint Staff headquarters that oversees and coordinates the operations of the French Armed Forces.
  • C. EMA
    EMA is the European Union’s regulatory authority responsible for the scientific evaluation, supervision, and safety monitoring of medicines.
  • D. Em
    Em is a common shortened form of the given name Emma, often used as an informal nickname.
  • E. ENM
    ENM is the commonly used abbreviation for the Naval Military School (Escuela Naval Militar), the institution responsible for training naval officers.
  • 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: EMA
Triple: [Navy Staff of Spain, abbreviation, EMA]
Generated description
EMA is the acronym for the Spanish Navy Staff, the central command body responsible for directing and managing Spain’s naval forces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EMA
Target entity description: EMA is the acronym for the Spanish Navy Staff, the central command body responsible for directing and managing Spain’s naval forces.
  • A. EMA
    EMA is the European Union’s regulatory authority responsible for the scientific evaluation, supervision, and safety monitoring of medicines.
  • B. EMA
    EMA is the three-letter IATA airport code for East Midlands Airport in England, which serves the East Midlands region with domestic and international flights.
  • C. EMA
    EMA is the abbreviated name for the Joint Staff headquarters that oversees and coordinates the operations of the French Armed Forces.
  • D. Em
    Em is a common shortened form of the given name Emma, often used as an informal nickname.
  • E. ENM
    ENM is the commonly used abbreviation for the Naval Military School (Escuela Naval Militar), the institution responsible for training naval officers.
  • 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_69ca84d7260c8190bfbec36762943f37 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded3566f881909e0d1366f501d554 completed April 2, 2026, 4:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3179b9de88190ba3beb7d6dbf7ad3 completed April 6, 2026, 2:16 a.m.
NEDg Description generation batch_69d318d099648190a42fffec876711dd completed April 6, 2026, 2:22 a.m.
NED2 Entity disambiguation (via description) batch_69d3194331c481909b8ef2dead8ed105 completed April 6, 2026, 2:24 a.m.
Created at: March 30, 2026, 9:12 p.m.