Triple

T26969094
Position Surface form Disambiguated ID Type / Status
Subject Esther de Berdt Reed E679256 entity
Predicate birthName P65 FINISHED
Object Esther de Berdt
Esther de Berdt was an English-born patriot and civic leader in Philadelphia who organized women’s support for the American Revolutionary War, notably through fundraising and supplying the Continental Army.
E1753065 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: Esther de Berdt | Statement: [Esther de Berdt Reed, birthName, Esther de Berdt]
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: Esther de Berdt
Triple: [Esther de Berdt Reed, birthName, Esther de Berdt]
Generated description
Esther de Berdt was an English-born patriot and civic leader in Philadelphia who organized women’s support for the American Revolutionary War, notably through fundraising and supplying the Continental Army.

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_69eeeb4f3a448190b1e94b2d4776c16e completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f621233f2c81908c237f20c50c2ba3 completed May 2, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123aaa71588190b25f802a3a182fc5 completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123b7235d081909cc231c0b1cc9b30 completed May 23, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_6a123c1061ac8190b8becdcf391832f8 completed May 23, 2026, 11:45 p.m.
Created at: April 27, 2026, 6:38 a.m.