Triple

T30793316
Position Surface form Disambiguated ID Type / Status
Subject James Spriggs Payne E784159 entity
Predicate spouse P13 FINISHED
Object Martha Ann White
Martha Ann White was the wife of James Spriggs Payne, a prominent Liberian politician and two-time president of Liberia in the 19th century.
 E1932241 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: Martha Ann White | Statement: [James Spriggs Payne, spouse, Martha Ann White]
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: Martha Ann White
Triple: [James Spriggs Payne, spouse, Martha Ann White]
Generated description
Martha Ann White was the wife of James Spriggs Payne, a prominent Liberian politician and two-time president of Liberia in the 19th 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_69f224b2e2a48190b19aa43db9da5b67 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6901035b88190ba857258707694cf completed May 3, 2026, midnight
NED1 Entity disambiguation (via context triple) batch_6a28b0ad88e48190b1a484920e132fc8 completed June 10, 2026, 12:32 a.m.
NEDg Description generation batch_6a28b1ed9b0c8190986159e58593fadf completed June 10, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a28b2b2c9fc8190af8deaeceb76e5f9 completed June 10, 2026, 12:41 a.m.
Created at: April 29, 2026, 8:42 p.m.