Triple

T27769485
Position Surface form Disambiguated ID Type / Status
Subject ACC Championship 2013 E701700 entity
Predicate notablePlayer_FloridaState P201888 FINISHED
Object Kelvin Benjamin
Kelvin Benjamin is an American football wide receiver best known for his standout college career at Florida State and his early NFL success with the Carolina Panthers.
E1788019 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: Kelvin Benjamin | Statement: [ACC Championship 2013, notablePlayer_FloridaState, Kelvin Benjamin]
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: Kelvin Benjamin
Triple: [ACC Championship 2013, notablePlayer_FloridaState, Kelvin Benjamin]
Generated description
Kelvin Benjamin is an American football wide receiver best known for his standout college career at Florida State and his early NFL success with the Carolina Panthers.

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_69ef6a52fa708190934a32308d2c92dc completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_6a002f56113c8190a75c77827b159f5b completed May 10, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12ecb9030881909e78ab07fc8505a3 completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12ed2afa9481909cc0ca56270ba2a0 completed May 24, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a12edccfe54819094da363072bdf7a6 completed May 24, 2026, 12:23 p.m.
Created at: April 27, 2026, 4:33 p.m.