Triple

T17265989
Position Surface form Disambiguated ID Type / Status
Subject Anne Gwynne E419127 entity
Predicate spouse P13 FINISHED
Object Max M. Gilford
Max M. Gilford was an American attorney and film industry figure best known as the husband of actress Anne Gwynne and the father of actor Gregory Peck’s first wife, Greta Kukkonen.
E1711636 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: Max M. Gilford | Statement: [Anne Gwynne, spouse, Max M. Gilford]
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: Max M. Gilford
Triple: [Anne Gwynne, spouse, Max M. Gilford]
Generated description
Max M. Gilford was an American attorney and film industry figure best known as the husband of actress Anne Gwynne and the father of actor Gregory Peck’s first wife, Greta Kukkonen.

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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42f44ec7c81909a925fc8692b0a6c completed April 19, 2026, 1:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1127101e8881909658e9196549e6e8 completed May 23, 2026, 4:03 a.m.
NEDg Description generation batch_6a113457b0d481909ae604a6947f0e36 completed May 23, 2026, 5 a.m.
NED2 Entity disambiguation (via description) batch_6a1134c87a5c8190b62dd699a5745362 completed May 23, 2026, 5:02 a.m.
Created at: April 10, 2026, 5:40 a.m.