Triple

T27087971
Position Surface form Disambiguated ID Type / Status
Subject Parvin Ardalan E686084 entity
Predicate movement P81 FINISHED
Object Iranian women's rights movement
The Iranian women's rights movement is a long-running social and political struggle in Iran aimed at achieving gender equality and reforming discriminatory laws and practices against women.
 E806215 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: Iranian women's rights movement | Statement: [Parvin Ardalan, movement, Iranian women's rights movement]
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: Iranian women's rights movement
Triple: [Parvin Ardalan, movement, Iranian women's rights movement]
Generated description
The Iranian women's rights movement is a long-running social and political struggle in Iran aimed at achieving gender equality and reforming discriminatory laws and practices against women.

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_69ef148940ec819097b5c20fbfbf7c81 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f6234735cc819097c3f109e724b0a4 completed May 2, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123ae3caf881909fb1447b52532be4 completed May 23, 2026, 11:40 p.m.
NEDg Description generation batch_6a123b72e22481909d5880a4b686b3e0 completed May 23, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_6a123c1995688190a630954191d4e905 completed May 23, 2026, 11:45 p.m.
Created at: April 27, 2026, 8:39 a.m.