Triple

T21746915
Position Surface form Disambiguated ID Type / Status
Subject Voices of a People’s History of the United States E536812 entity
Predicate editor P1954 FINISHED
Object Anthony Arnove
Anthony Arnove is an American author, editor, and filmmaker known for his collaborations with historian Howard Zinn and his work on radical and people's history.
E1719496 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: Anthony Arnove | Statement: [Voices of a People’s History of the United States, editor, Anthony Arnove]
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: Anthony Arnove
Triple: [Voices of a People’s History of the United States, editor, Anthony Arnove]
Generated description
Anthony Arnove is an American author, editor, and filmmaker known for his collaborations with historian Howard Zinn and his work on radical and people's history.

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_69e0c46df5448190b4322127ffc4c690 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01a771b908190886cade242e263e4 completed April 28, 2026, 2:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a118f6b6b8481908df3cb7d7ac8ca93 completed May 23, 2026, 11:28 a.m.
NEDg Description generation batch_6a119053e3b0819092c8e62b5b4ae02a completed May 23, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a1190db5ab48190a5b902fee03abdde completed May 23, 2026, 11:34 a.m.
Created at: April 16, 2026, 6:49 p.m.