Triple

T31359645
Position Surface form Disambiguated ID Type / Status
Subject Rinconete y Cortadillo E799828 entity
Predicate publisher P29 FINISHED
Object Juan de la Cuesta
Juan de la Cuesta was a prominent early 17th-century Madrid printer best known for producing the first editions of major works by Miguel de Cervantes.
E315621 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: Juan de la Cuesta | Statement: [Rinconete y Cortadillo, publisher, Juan de la Cuesta]
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: Juan de la Cuesta
Triple: [Rinconete y Cortadillo, publisher, Juan de la Cuesta]
Generated description
Juan de la Cuesta was a prominent early 17th-century Madrid printer best known for producing the first editions of major works by Miguel de Cervantes.

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_69f224e5e9bc8190a16339328897c4f8 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f4a00ac8190b7d9fa66781cef1f completed May 3, 2026, 1:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b1440c82081909e09b11ef444b9ff completed June 11, 2026, 8:02 p.m.
NEDg Description generation batch_6a2b16caba4c8190a0c21cabd7e9c032 completed June 11, 2026, 8:12 p.m.
NED2 Entity disambiguation (via description) batch_6a2b17192f788190a4bf2b77018892c6 completed June 11, 2026, 8:14 p.m.
Created at: April 29, 2026, 9:18 p.m.