Triple

T8914741
Position Surface form Disambiguated ID Type / Status
Subject NATO Rapid Deployable Corps Spain E212268 entity
Predicate locatedIn P40 FINISHED
Object Bétera
Bétera is a municipality in the province of Valencia, Spain, known for hosting a major NATO rapid deployment military headquarters.
 E765598 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: Bétera | Statement: [NATO Rapid Deployable Corps Spain, locatedIn, Bétera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bétera
Context triple: [NATO Rapid Deployable Corps Spain, locatedIn, Bétera]
  • A. Arisbe
    Arisbe is a figure in Greek mythology known as an early wife of King Priam of Troy.
  • B. Erquito
    Erquito is a small locality within the municipality of Alajeró on the island of La Gomera in Spain’s Canary Islands.
  • C. Garamas
    Garamas is a minor figure in Greek mythology known primarily as a descendant of the Cretan princess Acacallis.
  • D. Báguanos
    Báguanos is a municipality in eastern Cuba located in the province of Holguín, known for its agricultural activities and rural communities.
  • E. Basto
    Basto is a subregion of Portugal’s Vinho Verde wine area, known for producing fresh, often slightly effervescent white wines from indigenous grape varieties.
  • 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: Bétera
Triple: [NATO Rapid Deployable Corps Spain, locatedIn, Bétera]
Generated description
Bétera is a municipality in the province of Valencia, Spain, known for hosting a major NATO rapid deployment military headquarters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bétera
Target entity description: Bétera is a municipality in the province of Valencia, Spain, known for hosting a major NATO rapid deployment military headquarters.
  • A. Arisbe
    Arisbe is a figure in Greek mythology known as an early wife of King Priam of Troy.
  • B. Erquito
    Erquito is a small locality within the municipality of Alajeró on the island of La Gomera in Spain’s Canary Islands.
  • C. Garamas
    Garamas is a minor figure in Greek mythology known primarily as a descendant of the Cretan princess Acacallis.
  • D. Báguanos
    Báguanos is a municipality in eastern Cuba located in the province of Holguín, known for its agricultural activities and rural communities.
  • E. Basto
    Basto is a subregion of Portugal’s Vinho Verde wine area, known for producing fresh, often slightly effervescent white wines from indigenous grape varieties.
  • 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_69ca8393b1808190bd4336787ffa2c40 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc660e620c8190b02b9843c8f02bfa completed April 1, 2026, 12:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba4102e881908441669e14e5c491 completed April 3, 2026, 1:01 p.m.
NEDg Description generation batch_69cfbacea9408190a38f14817437c382 completed April 3, 2026, 1:04 p.m.
NED2 Entity disambiguation (via description) batch_69cfbb6235148190850865a734d55a6c completed April 3, 2026, 1:06 p.m.
Created at: March 30, 2026, 6:56 p.m.