Triple

T25268201
Position Surface form Disambiguated ID Type / Status
Subject John Archer Elmore E633489 entity
Predicate spouse P13 FINISHED
Object Nancy Ann Martin
Nancy Ann Martin was the wife of American Revolutionary War officer and Alabama politician John Archer Elmore.
E1692135 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: Nancy Ann Martin | Statement: [John Archer Elmore, spouse, Nancy Ann Martin]
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: Nancy Ann Martin
Triple: [John Archer Elmore, spouse, Nancy Ann Martin]
Generated description
Nancy Ann Martin was the wife of American Revolutionary War officer and Alabama politician John Archer Elmore.

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_69e75a92f48881909974ff9c11150a2e completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f48b9ea0e0819086d44dc5f6a2bd55 completed May 1, 2026, 11:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10c117961081908a667d2053857a3d completed May 22, 2026, 8:48 p.m.
NEDg Description generation batch_6a10c4eb37cc8190b7c3440b77e8336e completed May 22, 2026, 9:04 p.m.
NED2 Entity disambiguation (via description) batch_6a10c5487a008190aa865554f445ab5e completed May 22, 2026, 9:06 p.m.
Created at: April 21, 2026, 1:16 p.m.