Triple

T33317290
Position Surface form Disambiguated ID Type / Status
Subject Silent Sentinels E853046 entity
Predicate participant P858 FINISHED
Object Eunice Dana Brannan
Eunice Dana Brannan was an American suffragist and women's rights activist known for her role in the Silent Sentinels protests for women's voting rights in the early 20th century.
E2147971 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: Eunice Dana Brannan | Statement: [Silent Sentinels, participant, Eunice Dana Brannan]
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: Eunice Dana Brannan
Triple: [Silent Sentinels, participant, Eunice Dana Brannan]
Generated description
Eunice Dana Brannan was an American suffragist and women's rights activist known for her role in the Silent Sentinels protests for women's voting rights in the early 20th century.

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_69f349685f088190b8fda44083a018a9 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6defce7608190a3aab8225977f6da completed May 3, 2026, 5:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a385bb4813c819083d35f3c6c893e60 completed June 21, 2026, 9:46 p.m.
NEDg Description generation batch_6a385d888df88190b44e461ec36ffdeb completed June 21, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_6a3861536a7881909e260a0e6283cfc0 completed June 21, 2026, 10:10 p.m.
Created at: May 1, 2026, 1:33 a.m.