Triple

T27294260
Position Surface form Disambiguated ID Type / Status
Subject Garrett Reid E688716 entity
Predicate relative P37 FINISHED
Object NFL coach Britt Reid
Britt Reid is an American football coach best known as the son of longtime NFL head coach Andy Reid and for serving as an assistant coach with the Kansas City Chiefs.
E1767641 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: NFL coach Britt Reid | Statement: [Garrett Reid, relative, NFL coach Britt Reid]
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: NFL coach Britt Reid
Triple: [Garrett Reid, relative, NFL coach Britt Reid]
Generated description
Britt Reid is an American football coach best known as the son of longtime NFL head coach Andy Reid and for serving as an assistant coach with the Kansas City Chiefs.

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_69ef355a96308190a2bed991525fb278 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6277e806c819085dbcbddb9d86af1 completed May 2, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129ca5733c8190aeffec269245a947 completed May 24, 2026, 6:37 a.m.
NEDg Description generation batch_6a129ddafd888190a98657a4d9046d5c completed May 24, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_6a129e5f7e348190af4a279de8ef8caa completed May 24, 2026, 6:44 a.m.
Created at: April 27, 2026, 11:17 a.m.