Triple

T29609905
Position Surface form Disambiguated ID Type / Status
Subject Pas and Miera valleys E754685 entity
Predicate knownFor P22 FINISHED
Object Pasiego cabins
Pasiego cabins are traditional stone-and-wood shepherd dwellings in northern Spain’s Pas and Miera valleys, emblematic of the region’s rural pastoral culture and landscape.
E1875605 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: Pasiego cabins | Statement: [Pas and Miera valleys, knownFor, Pasiego cabins]
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: Pasiego cabins
Triple: [Pas and Miera valleys, knownFor, Pasiego cabins]
Generated description
Pasiego cabins are traditional stone-and-wood shepherd dwellings in northern Spain’s Pas and Miera valleys, emblematic of the region’s rural pastoral culture and landscape.

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_69f0ef85f62081909842b59fdf8717e1 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66dea375881909684db997861425c completed May 2, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a262d8911c88190a725e41f78ac9717 completed June 8, 2026, 2:48 a.m.
NEDg Description generation batch_6a26318fba948190a7676b94a96e2385 completed June 8, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a2635ad095481909c2fbed70b7a5f4c completed June 8, 2026, 3:23 a.m.
Created at: April 28, 2026, 6:27 p.m.