Triple

T8005942
Position Surface form Disambiguated ID Type / Status
Subject David Villa E186363 entity
Predicate youthClub P1088 FINISHED
Object Langreo
Langreo is a town in Asturias, Spain, known in football for being one of the early youth clubs of striker David Villa.
 E701737 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: Langreo | Statement: [David Villa, youthClub, Langreo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Langreo
Context triple: [David Villa, youthClub, Langreo]
  • A. Salen
    Salen is a small coastal village on the Isle of Mull in Scotland, known as a local hub with basic services for residents and visitors exploring the island.
  • B. Berriane
    Berriane is a town in Algeria known as part of the historic M’zab oasis region, characterized by its traditional architecture and Saharan environment.
  • C. Balasinor
    Balasinor is a town in Gujarat, India, known for its nearby dinosaur fossil park and rich paleontological significance.
  • D. Anoia
    Anoia is a comarca (county) in central Catalonia, Spain, known for its mix of industrial towns and rural landscapes, with Igualada as its capital.
  • E. Lierne
    Lierne is a sparsely populated municipality in Trøndelag county, Norway, known for its vast wilderness areas, national parks, and rich wildlife.
  • 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: Langreo
Triple: [David Villa, youthClub, Langreo]
Generated description
Langreo is a town in Asturias, Spain, known in football for being one of the early youth clubs of striker David Villa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Langreo
Target entity description: Langreo is a town in Asturias, Spain, known in football for being one of the early youth clubs of striker David Villa.
  • A. Salen
    Salen is a small coastal village on the Isle of Mull in Scotland, known as a local hub with basic services for residents and visitors exploring the island.
  • B. Berriane
    Berriane is a town in Algeria known as part of the historic M’zab oasis region, characterized by its traditional architecture and Saharan environment.
  • C. Balasinor
    Balasinor is a town in Gujarat, India, known for its nearby dinosaur fossil park and rich paleontological significance.
  • D. Anoia
    Anoia is a comarca (county) in central Catalonia, Spain, known for its mix of industrial towns and rural landscapes, with Igualada as its capital.
  • E. Lierne
    Lierne is a sparsely populated municipality in Trøndelag county, Norway, known for its vast wilderness areas, national parks, and rich wildlife.
  • 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_69ca82aaaf24819084b94d18f699ba53 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3cf72fc08190aa78b97c1ab92f90 completed March 31, 2026, 3:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe12c068c8190a6ea7e924a7748c6 completed March 31, 2026, 2:58 p.m.
NEDg Description generation batch_69cbe442999881909544802bb9a91cd5 completed March 31, 2026, 3:12 p.m.
NED2 Entity disambiguation (via description) batch_69cc09c676148190964d4947310ec16a completed March 31, 2026, 5:52 p.m.
Created at: March 30, 2026, 5:18 p.m.