Triple

T24859054
Position Surface form Disambiguated ID Type / Status
Subject Enrique Vila-Matas E622104 entity
Predicate notableWork P4 FINISHED
Object Doctor Pasavento
Doctor Pasavento is a metafictional novel by Enrique Vila-Matas that explores themes of identity, disappearance, and the act of writing through the story of a writer who gradually erases himself from the world.
E1649460 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: Doctor Pasavento | Statement: [Enrique Vila-Matas, notableWork, Doctor Pasavento]
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: Doctor Pasavento
Triple: [Enrique Vila-Matas, notableWork, Doctor Pasavento]
Generated description
Doctor Pasavento is a metafictional novel by Enrique Vila-Matas that explores themes of identity, disappearance, and the act of writing through the story of a writer who gradually erases himself from the world.

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_69e2fac350d08190b3affde1b451a8c5 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422eae9588190b3b9c8d4710c9bd4 completed May 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c571d0c8190bada500ce9fcfbf9 completed May 22, 2026, 9:05 a.m.
NEDg Description generation batch_6a10229229a481909ebb009ce5932e8b completed May 22, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_6a102388612c81909fda138f132409a3 completed May 22, 2026, 9:36 a.m.
Created at: April 18, 2026, 5:21 a.m.