Triple

T35600404
Position Surface form Disambiguated ID Type / Status
Subject Bob Sapp E1028748 entity
Predicate competedIn P149 FINISHED
Object Hustle (wrestling promotion)
Hustle (stylized as HUSTLE) was a Japanese professional wrestling promotion known for its sports entertainment–style shows, over-the-top characters, and emphasis on spectacle and comedy.
E2148524 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: Hustle (wrestling promotion) | Statement: [Bob Sapp, competedIn, Hustle (wrestling promotion)]
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: Hustle (wrestling promotion)
Triple: [Bob Sapp, competedIn, Hustle (wrestling promotion)]
Generated description
Hustle (stylized as HUSTLE) was a Japanese professional wrestling promotion known for its sports entertainment–style shows, over-the-top characters, and emphasis on spectacle and comedy.

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_69f76e0598dc8190a6a093e904b9aa70 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79eac067481909d658466274819fb completed May 3, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a385be0ee1481908a9db8e936ead685 completed June 21, 2026, 9:47 p.m.
NEDg Description generation batch_6a385cd2f1248190a26ee3bdc77db301 completed June 21, 2026, 9:51 p.m.
NED2 Entity disambiguation (via description) batch_6a3860e6f4c48190bc96b1c4d289e650 completed June 21, 2026, 10:08 p.m.
Created at: May 3, 2026, 4:05 p.m.