Triple

T28129840
Position Surface form Disambiguated ID Type / Status
Subject Beauty No. 2 E711034 entity
Predicate castMember P1668 FINISHED
Object Gino Piserchio
Gino Piserchio was an American actor and musician associated with Andy Warhol’s avant-garde film scene in the 1960s.
E2296285 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: Gino Piserchio | Statement: [Beauty No. 2, castMember, Gino Piserchio]
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: Gino Piserchio
Triple: [Beauty No. 2, castMember, Gino Piserchio]
Generated description
Gino Piserchio was an American actor and musician associated with Andy Warhol’s avant-garde film scene in the 1960s.

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_69ef9b73bd288190a21ae3d6aa14f386 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f640ff720c8190a6edb7f6b5dd5b7e completed May 2, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a825a8b6ccc81908fb5f2a9e67323c0 completed Aug. 17, 2026, 12:49 a.m.
NEDg Description generation batch_6a825add19688190a6416c13e33c18d8 completed Aug. 17, 2026, 12:50 a.m.
NED2 Entity disambiguation (via description) batch_6a825b2f781c8190bd7bd46e2298ad59 completed Aug. 17, 2026, 12:51 a.m.
Created at: April 27, 2026, 9:22 p.m.