Triple

T36746119
Position Surface form Disambiguated ID Type / Status
Subject City of Lorca E907768 entity
Predicate hasComarca P33339 FINISHED
Object Alto Guadalentín
Alto Guadalentín is a comarca in the Region of Murcia in southeastern Spain, centered around the city of Lorca and known for its agricultural plains along the upper Guadalentín River.
E2196868 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: Alto Guadalentín | Statement: [City of Lorca, hasComarca, Alto Guadalentín]
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: Alto Guadalentín
Triple: [City of Lorca, hasComarca, Alto Guadalentín]
Generated description
Alto Guadalentín is a comarca in the Region of Murcia in southeastern Spain, centered around the city of Lorca and known for its agricultural plains along the upper Guadalentín River.

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_69f76e76d10881909ec1679bc043108c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c93ea53481909a5e742cc41adb7e completed May 3, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3c17335fdc8190b231044eb5670227 completed June 24, 2026, 5:43 p.m.
NEDg Description generation batch_6a3c18778cb481909d7ec4ae70f940bc completed June 24, 2026, 5:48 p.m.
NED2 Entity disambiguation (via description) batch_6a3c53462a408190bb8da22eda8576de completed June 24, 2026, 9:59 p.m.
Created at: May 3, 2026, 4:12 p.m.