Triple

T32089743
Position Surface form Disambiguated ID Type / Status
Subject Huércal-Overa E819555 entity
Predicate locatedIn P40 FINISHED
Object Comarca of Levante Almeriense
The Comarca of Levante Almeriense is a coastal and inland region in the eastern part of Spain’s Almería province, known for its agriculture, tourism, and growing residential communities.
E1991199 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: Comarca of Levante Almeriense | Statement: [Huércal-Overa, locatedIn, Comarca of Levante Almeriense]
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: Comarca of Levante Almeriense
Triple: [Huércal-Overa, locatedIn, Comarca of Levante Almeriense]
Generated description
The Comarca of Levante Almeriense is a coastal and inland region in the eastern part of Spain’s Almería province, known for its agriculture, tourism, and growing residential communities.

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_69f349004b2481908ce2e50af0d579a8 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b63ca23c8190a0c03db580d774f9 completed May 3, 2026, 2:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2eddf36e6c8190b774fdf0a5dbbe4f completed June 14, 2026, 4:59 p.m.
NEDg Description generation batch_6a2ee0a2f4948190825bfd886ccce442 completed June 14, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_6a2ee1551e4c8190b227c870993b6b6a completed June 14, 2026, 5:13 p.m.
Created at: May 1, 2026, 12:25 a.m.