Triple

T24050393
Position Surface form Disambiguated ID Type / Status
Subject Joaquín Vara del Rey y Rubio E595641 entity
Predicate relative P37 FINISHED
Object Julio Vara del Rey
Julio Vara del Rey was a member of the notable Spanish Vara del Rey family, related to the distinguished military officer Joaquín Vara del Rey y Rubio.
E1761915 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: Julio Vara del Rey | Statement: [Joaquín Vara del Rey y Rubio, relative, Julio Vara del Rey]
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: Julio Vara del Rey
Triple: [Joaquín Vara del Rey y Rubio, relative, Julio Vara del Rey]
Generated description
Julio Vara del Rey was a member of the notable Spanish Vara del Rey family, related to the distinguished military officer Joaquín Vara del Rey y Rubio.

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_69e288c184b081909f1f1751fb8e299a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d9cfb914819091a3378518f9f28d completed April 29, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12534dd3a88190aa1aae12a830a775 completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a12545544f881909f0afd8459986559 completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a125879112c8190959380eaef8ccf19 completed May 24, 2026, 1:46 a.m.
Created at: April 17, 2026, 10:20 p.m.