Triple

T34097990
Position Surface form Disambiguated ID Type / Status
Subject Downtown 81 E874489 entity
Predicate castMember P1668 FINISHED
Object Walter Steding
Walter Steding is an American violinist, painter, and performance artist associated with New York’s 1970s–80s downtown art and punk scenes, known for collaborations with figures like Andy Warhol and Blondie.
E2176034 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: Walter Steding | Statement: [Downtown 81, castMember, Walter Steding]
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: Walter Steding
Triple: [Downtown 81, castMember, Walter Steding]
Generated description
Walter Steding is an American violinist, painter, and performance artist associated with New York’s 1970s–80s downtown art and punk scenes, known for collaborations with figures like Andy Warhol and Blondie.

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_69f349a735208190a1dbfb1c2a121059 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70c6153e48190879589fa9eab790f completed May 3, 2026, 8:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a396de8189081908c1df6654fdca1a3 completed June 22, 2026, 5:16 p.m.
NEDg Description generation batch_6a396ed615e88190afc150b7ad4121ef completed June 22, 2026, 5:20 p.m.
NED2 Entity disambiguation (via description) batch_6a396fd681a88190a687284b93b848d1 completed June 22, 2026, 5:24 p.m.
Created at: May 1, 2026, 1:53 a.m.