Triple

T30214889
Position Surface form Disambiguated ID Type / Status
Subject Yvonne Rainer E768176 entity
Predicate notableWork P4 FINISHED
Object The Man Who Envied Women
The Man Who Envied Women is an experimental feminist film by Yvonne Rainer that critiques gender, power, and representation through a fragmented, essayistic narrative style.
 E1903893 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 Man Who Envied Women | Statement: [Yvonne Rainer, notableWork, The Man Who Envied Women]
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 Man Who Envied Women
Triple: [Yvonne Rainer, notableWork, The Man Who Envied Women]
Generated description
The Man Who Envied Women is an experimental feminist film by Yvonne Rainer that critiques gender, power, and representation through a fragmented, essayistic narrative style.

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_69f2247fd8b8819087fcf83cb7a05eb8 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67ff517908190ad290edafd6c6f5f completed May 2, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2758eccc1c8190b297f1277d59cfa9 completed June 9, 2026, 12:06 a.m.
NEDg Description generation batch_6a275cf57eb88190a832298a147b55ad completed June 9, 2026, 12:23 a.m.
NED2 Entity disambiguation (via description) batch_6a275df157688190b30e56643dfb65d8 completed June 9, 2026, 12:27 a.m.
Created at: April 29, 2026, 7:33 p.m.