Triple

T32281753
Position Surface form Disambiguated ID Type / Status
Subject Howard Estabrook E824712 entity
Predicate spouse P13 FINISHED
Object Margaret Estabrook
Margaret Estabrook was the wife of American screenwriter, film producer, and actor Howard Estabrook.
E2062169 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: Margaret Estabrook | Statement: [Howard Estabrook, spouse, Margaret Estabrook]
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: Margaret Estabrook
Triple: [Howard Estabrook, spouse, Margaret Estabrook]
Generated description
Margaret Estabrook was the wife of American screenwriter, film producer, and actor Howard Estabrook.

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_69f3490f404081908450db66884f4334 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bccb5ea8819081b497d5667fa19a completed May 3, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3626f8659c8190880f1474bd96f51b completed June 20, 2026, 5:36 a.m.
NEDg Description generation batch_6a36279033e081909b97ac755ae90116 completed June 20, 2026, 5:39 a.m.
NED2 Entity disambiguation (via description) batch_6a362968a6c08190beb1123ec9f3b337 completed June 20, 2026, 5:47 a.m.
Created at: May 1, 2026, 12:43 a.m.