Triple

T35212253
Position Surface form Disambiguated ID Type / Status
Subject Lord of Arévalo de la Sierra E1016714 entity
Predicate associatedWithTerritory P12445 FINISHED
Object Arévalo de la Sierra
Arévalo de la Sierra is a small municipality in the province of Soria, in the autonomous community of Castile and León, Spain.
E2131515 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: Arévalo de la Sierra | Statement: [Lord of Arévalo de la Sierra, associatedWithTerritory, Arévalo de la Sierra]
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: Arévalo de la Sierra
Triple: [Lord of Arévalo de la Sierra, associatedWithTerritory, Arévalo de la Sierra]
Generated description
Arévalo de la Sierra is a small municipality in the province of Soria, in the autonomous community of Castile and León, Spain.

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_69f76ddf549c8190869d0af076fd2c28 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78e74cedc8190b8afa7ea7171a93f completed May 3, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a380409ca5c8190b00dbd8509b9be7c completed June 21, 2026, 3:32 p.m.
NEDg Description generation batch_6a3804ad333081909c330fa860f3ac3c completed June 21, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a380651733c8190be3a7832419137da completed June 21, 2026, 3:42 p.m.
Created at: May 3, 2026, 4:02 p.m.