Triple

T36297915
Position Surface form Disambiguated ID Type / Status
Subject Muhammad Ali's Greatest Fight E893419 entity
Predicate executiveProducer P7225 FINISHED
Object Keri Putnam
Keri Putnam is an American film and television executive and producer best known for her leadership roles at HBO Films, Miramax, and as CEO of the Sundance Institute.
E2184587 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: Keri Putnam | Statement: [Muhammad Ali's Greatest Fight, executiveProducer, Keri Putnam]
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: Keri Putnam
Triple: [Muhammad Ali's Greatest Fight, executiveProducer, Keri Putnam]
Generated description
Keri Putnam is an American film and television executive and producer best known for her leadership roles at HBO Films, Miramax, and as CEO of the Sundance Institute.

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_69f76e4a61f0819084a2b68dbbb4efc6 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7ba0121ac8190baf59381692a264a completed May 3, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c3f50c4481909aef4c60f5be52a8 completed June 22, 2026, 11:23 p.m.
NEDg Description generation batch_6a39c5ba1a5c8190827e09d608eac04f completed June 22, 2026, 11:31 p.m.
NED2 Entity disambiguation (via description) batch_6a39c9af2e6481909469e1fb9d3de72a completed June 22, 2026, 11:47 p.m.
Created at: May 3, 2026, 4:09 p.m.