Triple

T30837875
Position Surface form Disambiguated ID Type / Status
Subject Laurinburg Institute E785412 entity
Predicate hasAlumni P51 FINISHED
Object Korleone Young
Korleone Young is an American former professional basketball player best known for jumping directly from high school to the NBA when he was drafted by the Detroit Pistons in 1998.
E1933178 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: Korleone Young | Statement: [Laurinburg Institute, hasAlumni, Korleone Young]
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: Korleone Young
Triple: [Laurinburg Institute, hasAlumni, Korleone Young]
Generated description
Korleone Young is an American former professional basketball player best known for jumping directly from high school to the NBA when he was drafted by the Detroit Pistons in 1998.

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_69f224b73d8c81908129383bfb397c87 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69140dcfc8190aeb557a6c788234c completed May 3, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbf2e0288190adcde597d0ebf031 completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bc947d108190801b827472733dfa completed June 10, 2026, 1:23 a.m.
NED2 Entity disambiguation (via description) batch_6a28bd11752881909989925c16498f98 completed June 10, 2026, 1:25 a.m.
Created at: April 29, 2026, 8:45 p.m.