Triple

T31952361
Position Surface form Disambiguated ID Type / Status
Subject Michele Landsberg E815812 entity
Predicate notableWork P4 FINISHED
Object Writing the Revolution
"Writing the Revolution" is a landmark collection of feminist journalism and commentary by Canadian writer and activist Michele Landsberg, chronicling decades of social and political change.
 E1984560 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: Writing the Revolution | Statement: [Michele Landsberg, notableWork, Writing the Revolution]
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: Writing the Revolution
Triple: [Michele Landsberg, notableWork, Writing the Revolution]
Generated description
"Writing the Revolution" is a landmark collection of feminist journalism and commentary by Canadian writer and activist Michele Landsberg, chronicling decades of social and political change.

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_69f348f4ec708190abbb2a7c3ed58844 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b2ac9bd481909a1e8adb4e294262 completed May 3, 2026, 2:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e8a4bf8f881908d751241b633f64a completed June 14, 2026, 11:02 a.m.
NEDg Description generation batch_6a2e8aba8d9481908df3439168b0f62f completed June 14, 2026, 11:04 a.m.
NED2 Entity disambiguation (via description) batch_6a2e8b6f6f2c819098e1787c61964edd completed June 14, 2026, 11:07 a.m.
Created at: May 1, 2026, 12:07 a.m.