Triple

T30647936
Position Surface form Disambiguated ID Type / Status
Subject Sierra de Francia E780174 entity
Predicate contains P35 FINISHED
Object Miranda del Castañar
Miranda del Castañar is a historic fortified village in western Spain’s Salamanca province, known for its well-preserved medieval walls, castle, and traditional architecture within the Sierra de Francia region.
E1945610 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: Miranda del Castañar | Statement: [Sierra de Francia, contains, Miranda del Castañar]
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: Miranda del Castañar
Triple: [Sierra de Francia, contains, Miranda del Castañar]
Generated description
Miranda del Castañar is a historic fortified village in western Spain’s Salamanca province, known for its well-preserved medieval walls, castle, and traditional architecture within the Sierra de Francia region.

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_69f224a5d2b481908a6853cd0138e2d7 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68a9537fc819083849c707a8add46 completed May 2, 2026, 11:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a292af179e48190814fa521f8ea348c completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292f50e6288190acec97b1ec8ccfcb completed June 10, 2026, 9:33 a.m.
NED2 Entity disambiguation (via description) batch_6a2930b369f4819082c70a68175249b8 completed June 10, 2026, 9:38 a.m.
Created at: April 29, 2026, 8:29 p.m.