Triple

T28870552
Position Surface form Disambiguated ID Type / Status
Subject Frank Beamer E732128 entity
Predicate successor P78 FINISHED
Object Justin Fuente (as Virginia Tech head coach)
Justin Fuente is an American college football coach who led the Virginia Tech Hokies after a successful stint revitalizing the Memphis program.
E1837800 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: Justin Fuente (as Virginia Tech head coach) | Statement: [Frank Beamer, successor, Justin Fuente (as Virginia Tech head coach)]
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: Justin Fuente (as Virginia Tech head coach)
Triple: [Frank Beamer, successor, Justin Fuente (as Virginia Tech head coach)]
Generated description
Justin Fuente is an American college football coach who led the Virginia Tech Hokies after a successful stint revitalizing the Memphis program.

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_69f05b06807c81909b4bbd4c20403a2b completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65a46a2a881908b8d2dba7cfb108b completed May 2, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bbc815b481908c4b517a4b53eae2 completed June 7, 2026, 12:31 a.m.
NEDg Description generation batch_6a24bfdddd108190b1f48a0317754806 completed June 7, 2026, 12:48 a.m.
NED2 Entity disambiguation (via description) batch_6a24c40832a881908ca8c2d0b09b1458 completed June 7, 2026, 1:06 a.m.
Created at: April 28, 2026, 7:32 a.m.