Triple

T33941501
Position Surface form Disambiguated ID Type / Status
Subject Beijing Royal Fighters E870177 entity
Predicate notablePlayer P304 FINISHED
Object Kyle Fogg
Kyle Fogg is an American professional basketball player known as a high-scoring guard who has starred in various international leagues, particularly in the Chinese Basketball Association.
E2089756 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: Kyle Fogg | Statement: [Beijing Royal Fighters, notablePlayer, Kyle Fogg]
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: Kyle Fogg
Triple: [Beijing Royal Fighters, notablePlayer, Kyle Fogg]
Generated description
Kyle Fogg is an American professional basketball player known as a high-scoring guard who has starred in various international leagues, particularly in the Chinese Basketball Association.

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_69f3499b0dd48190b07b4b60babcee02 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f702369cf881909f9465ce9a48fd2d completed May 3, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36e6066d848190a7dc3dc945d69166 completed June 20, 2026, 7:12 p.m.
NEDg Description generation batch_6a36e89ff0808190a49ce53dc21e3491 completed June 20, 2026, 7:23 p.m.
NED2 Entity disambiguation (via description) batch_6a36e91e81f08190b7ff33ec87865f33 completed June 20, 2026, 7:25 p.m.
Created at: May 1, 2026, 1:49 a.m.