Triple

T34263973
Position Surface form Disambiguated ID Type / Status
Subject Lowell Thomas E879111 entity
Predicate spouse P13 FINISHED
Object Frances Ryan
Frances Ryan was the wife of American broadcaster and explorer Lowell Thomas, known primarily in relation to his personal life.
E2130489 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: Frances Ryan | Statement: [Lowell Thomas, spouse, Frances Ryan]
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: Frances Ryan
Triple: [Lowell Thomas, spouse, Frances Ryan]
Generated description
Frances Ryan was the wife of American broadcaster and explorer Lowell Thomas, known primarily in relation to his personal life.

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_69f349b4f5fc819094b441d18e95e5f1 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f712c3cbe88190bdae67ad1c2ce195 completed May 3, 2026, 9:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3803e75bd081908aad28ab9c921d0a completed June 21, 2026, 3:31 p.m.
NEDg Description generation batch_6a3804c6a8788190ac07c698d78a290d completed June 21, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a38057811848190a12d3e760db65b2d completed June 21, 2026, 3:38 p.m.
Created at: May 1, 2026, 1:56 a.m.