Triple

T23706099
Position Surface form Disambiguated ID Type / Status
Subject Sam Wyche E585724 entity
Predicate fullName P16 FINISHED
Object Samuel David Wyche
Samuel David Wyche was an American football coach and former NFL quarterback best known for coaching the Cincinnati Bengals to a Super Bowl appearance and for his innovative no-huddle offense.
E1614388 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: Samuel David Wyche | Statement: [Sam Wyche, fullName, Samuel David Wyche]
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: Samuel David Wyche
Triple: [Sam Wyche, fullName, Samuel David Wyche]
Generated description
Samuel David Wyche was an American football coach and former NFL quarterback best known for coaching the Cincinnati Bengals to a Super Bowl appearance and for his innovative no-huddle offense.

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_69e24905f77881908194d645676acd60 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b687ae708190a9233100a9e0204f completed April 29, 2026, 7:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e4ef4d88190b91dfc4f6c4713c1 completed May 21, 2026, 9:51 p.m.
NEDg Description generation batch_6a0f7fc0bd54819095d6de5f3e9aa6dd completed May 21, 2026, 9:57 p.m.
NED2 Entity disambiguation (via description) batch_6a0f808b2da08190ae7822611c8c1939 completed May 21, 2026, 10 p.m.
Created at: April 17, 2026, 6:53 p.m.