Triple

T20916133
Position Surface form Disambiguated ID Type / Status
Subject Eo-Navia region E515077 entity
Predicate contains P35 FINISHED
Object El Franco
El Franco is a coastal municipality in the Asturias region of northern Spain, known for its rugged shoreline and rural landscapes.
 E1457049 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: El Franco | Statement: [Eo-Navia region, contains, El Franco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: El Franco
Context triple: [Eo-Navia region, contains, El Franco]
  • A. Le François
    Le François is a coastal commune on the eastern side of Martinique in the French Caribbean, known for its sheltered bays, islets, and traditional fishing and agricultural activities.
  • B. Franca
    Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
  • C. Le Bry
    Le Bry is a Swiss municipality located in the canton of Fribourg, known for its proximity to the scenic Lake of Gruyère in the Gruyère region.
  • D. Fraimbois
    Fraimbois is a small commune in the Meurthe-et-Moselle department in northeastern France.
  • E. Guichen
    Guichen was a French admiral, Luc Urbain de Bouëxic, comte de Guichen, noted for commanding French naval forces during the American Revolutionary War.
  • 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: El Franco
Triple: [Eo-Navia region, contains, El Franco]
Generated description
El Franco is a coastal municipality in the Asturias region of northern Spain, known for its rugged shoreline and rural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: El Franco
Target entity description: El Franco is a coastal municipality in the Asturias region of northern Spain, known for its rugged shoreline and rural landscapes.
  • A. Le François
    Le François is a coastal commune on the eastern side of Martinique in the French Caribbean, known for its sheltered bays, islets, and traditional fishing and agricultural activities.
  • B. Franca
    Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
  • C. Le Bry
    Le Bry is a Swiss municipality located in the canton of Fribourg, known for its proximity to the scenic Lake of Gruyère in the Gruyère region.
  • D. Fraimbois
    Fraimbois is a small commune in the Meurthe-et-Moselle department in northeastern France.
  • E. Guichen
    Guichen was a French admiral, Luc Urbain de Bouëxic, comte de Guichen, noted for commanding French naval forces during the American Revolutionary War.
  • 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_69e0b4f9d5ec8190bb2bd27350ed341c completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6ec628a38819093dcb70de91c770b completed April 21, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0918e0178081908c271dc800de798e completed May 17, 2026, 1:24 a.m.
NEDg Description generation batch_6a091be2f1208190a57e7f7d8aabddc0 completed May 17, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_6a091c47b3dc81908a5188ad63e14ec6 completed May 17, 2026, 1:39 a.m.
Created at: April 16, 2026, 12:48 p.m.