Triple

T35951968
Position Surface form Disambiguated ID Type / Status
Subject The King and Four Queens E1039752 entity
Predicate producer P490 FINISHED
Object Robert Waterfield
Robert Waterfield was an American film producer and former professional football quarterback who co-produced several films starring his wife, actress Jane Russell.
E2162685 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: Robert Waterfield | Statement: [The King and Four Queens, producer, Robert Waterfield]
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: Robert Waterfield
Triple: [The King and Four Queens, producer, Robert Waterfield]
Generated description
Robert Waterfield was an American film producer and former professional football quarterback who co-produced several films starring his wife, actress Jane Russell.

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_69f76e25ea488190b7cee970b3e70382 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7abd758648190a20db71b31002648 completed May 3, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38b6ff63c48190baa1803c2bce5fa7 completed June 22, 2026, 4:15 a.m.
NEDg Description generation batch_6a38b79ce030819097ca219bbf6e7b73 completed June 22, 2026, 4:18 a.m.
NED2 Entity disambiguation (via description) batch_6a38b82ae47c81909d15314df525054a completed June 22, 2026, 4:20 a.m.
Created at: May 3, 2026, 4:07 p.m.