Triple

T31226105
Position Surface form Disambiguated ID Type / Status
Subject Sierra de Cameros E796141 entity
Predicate hasSettlement P1068 FINISHED
Object Ortigosa de Cameros
Ortigosa de Cameros is a small mountain village and municipality in La Rioja, northern Spain, known for its scenic setting in the Sierra de Cameros and nearby limestone caves.
E1954052 NE FINISHED

How this triple was built (2 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: Ortigosa de Cameros | Statement: [Sierra de Cameros, hasSettlement, Ortigosa de Cameros]
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: Ortigosa de Cameros
Triple: [Sierra de Cameros, hasSettlement, Ortigosa de Cameros]
Generated description
Ortigosa de Cameros is a small mountain village and municipality in La Rioja, northern Spain, known for its scenic setting in the Sierra de Cameros and nearby limestone caves.

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_69f224da98f88190ab32f690cce5d303 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69c50f4b481909d205c0a9807935e completed May 3, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a296bdfa2f88190a787895f93eaee6d completed June 10, 2026, 1:51 p.m.
NEDg Description generation batch_6a296fe7a5848190bb96205a6ede9dc2 completed June 10, 2026, 2:08 p.m.
NED2 Entity disambiguation (via description) batch_6a29a7f163ac819080e504a3bd158340 completed June 10, 2026, 6:07 p.m.
Created at: April 29, 2026, 9:10 p.m.