Triple

T34850459
Position Surface form Disambiguated ID Type / Status
Subject Ayo Dosunmu E1004586 entity
Predicate familyName P18 FINISHED
Object Dosunmu
Dosunmu is the surname of American professional basketball player Ayo Dosunmu, known for his collegiate career at Illinois and his NBA tenure with the Chicago Bulls.
E2115268 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: Dosunmu | Statement: [Ayo Dosunmu, familyName, Dosunmu]
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: Dosunmu
Triple: [Ayo Dosunmu, familyName, Dosunmu]
Generated description
Dosunmu is the surname of American professional basketball player Ayo Dosunmu, known for his collegiate career at Illinois and his NBA tenure with the Chicago Bulls.

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_69f76dba76f0819090643cba102c41ec completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7815cd9188190bc68635c1024b9a1 completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3779561db0819083cfd87dae8f191d completed June 21, 2026, 5:40 a.m.
NEDg Description generation batch_6a377a18f8308190851b20da04cabc34 completed June 21, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_6a377af6ab048190b572cefa83ec6dda completed June 21, 2026, 5:47 a.m.
Created at: May 3, 2026, 4 p.m.