Triple

T28030726
Position Surface form Disambiguated ID Type / Status
Subject Leuzinger High School E708257 entity
Predicate hasNotableAlumnus P51 FINISHED
Object Dorrell Wright
Dorrell Wright is an American former professional basketball player who played in the NBA, notably winning an NBA championship with the Miami Heat.
E1803042 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: Dorrell Wright | Statement: [Leuzinger High School, hasNotableAlumnus, Dorrell Wright]
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: Dorrell Wright
Triple: [Leuzinger High School, hasNotableAlumnus, Dorrell Wright]
Generated description
Dorrell Wright is an American former professional basketball player who played in the NBA, notably winning an NBA championship with the Miami Heat.

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_69ef9b6bdd9c8190bb3a574a03774ad1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63c72207481909a00938678ab7005 completed May 2, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c9045dd08190ad3dfc812a8dd89c completed May 26, 2026, 4:23 p.m.
NEDg Description generation batch_6a15ca9b9b888190a98c57af571fe49d completed May 26, 2026, 4:30 p.m.
NED2 Entity disambiguation (via description) batch_6a15cc3cef0c8190b7b5d6316dc2a9ff completed May 26, 2026, 4:37 p.m.
Created at: April 27, 2026, 8:16 p.m.