Triple

T31267283
Position Surface form Disambiguated ID Type / Status
Subject Cordillera Subbética E797286 entity
Predicate contains P35 FINISHED
Object Sierra de Loja
Sierra de Loja is a limestone mountain range in the province of Granada in southern Spain, known for its karst landscapes, caves, and rich biodiversity within the Subbaetic System.
E1953306 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: Sierra de Loja | Statement: [Cordillera Subbética, contains, Sierra de Loja]
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: Sierra de Loja
Triple: [Cordillera Subbética, contains, Sierra de Loja]
Generated description
Sierra de Loja is a limestone mountain range in the province of Granada in southern Spain, known for its karst landscapes, caves, and rich biodiversity within the Subbaetic System.

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_69f224de2bbc819081af6c32e1d857b9 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69d9243b48190b665977bd4729392 completed May 3, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a296bffdb688190bbf7988202c50a04 completed June 10, 2026, 1:52 p.m.
NEDg Description generation batch_6a296c9ac13c819081c06411d80071c1 completed June 10, 2026, 1:54 p.m.
NED2 Entity disambiguation (via description) batch_6a299c9b54dc8190abd715cd88979541 completed June 10, 2026, 5:19 p.m.
Created at: April 29, 2026, 9:13 p.m.