Triple

T30643218
Position Surface form Disambiguated ID Type / Status
Subject Martin Stanford Peters E780047 entity
Predicate spouse P13 FINISHED
Object Kathleen Peters
Kathleen Peters is known as the spouse of English footballer Martin Peters, a key member of England's 1966 World Cup–winning team.
 E1926184 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: Kathleen Peters | Statement: [Martin Stanford Peters, spouse, Kathleen Peters]
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: Kathleen Peters
Triple: [Martin Stanford Peters, spouse, Kathleen Peters]
Generated description
Kathleen Peters is known as the spouse of English footballer Martin Peters, a key member of England's 1966 World Cup–winning team.

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_69f224a50ebc81909b961a94c7f66b12 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68a57cc808190830b6ca9b5b83468 completed May 2, 2026, 11:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2870ecce7c8190b417e4f1b523a657 completed June 9, 2026, 8 p.m.
NEDg Description generation batch_6a2871b4b3308190a941e5e12ee67327 completed June 9, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_6a28721a8f7881908544f0d277189c34 completed June 9, 2026, 8:05 p.m.
Created at: April 29, 2026, 8:29 p.m.