Triple

T24020080
Position Surface form Disambiguated ID Type / Status
Subject Paul Virilio E594793 entity
Predicate notableWork P4 FINISHED
Object The Aesthetics of Disappearance
The Aesthetics of Disappearance is a philosophical work by Paul Virilio that explores how modern technologies of speed and media transform perception, presence, and the experience of time.
E1613482 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: The Aesthetics of Disappearance | Statement: [Paul Virilio, notableWork, The Aesthetics of Disappearance]
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: The Aesthetics of Disappearance
Triple: [Paul Virilio, notableWork, The Aesthetics of Disappearance]
Generated description
The Aesthetics of Disappearance is a philosophical work by Paul Virilio that explores how modern technologies of speed and media transform perception, presence, and the experience of time.

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_69e288be2c288190a3a46006945557f7 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d5a925208190badd075519a0f4b6 completed April 29, 2026, 9:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7ea5d23c8190b911c1c063668bdf completed May 21, 2026, 9:52 p.m.
NEDg Description generation batch_6a0f7f4e4b9081909cf4a5a60f4da17f completed May 21, 2026, 9:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0f803e39408190b612e1bade70bac2 completed May 21, 2026, 9:59 p.m.
Created at: April 17, 2026, 9:43 p.m.