Triple

T6663929
Position Surface form Disambiguated ID Type / Status
Subject Rasheed E151546 entity
Predicate hasNotableBearer P458 FINISHED
Object Rasheed Wallace E28016 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: Rasheed Wallace | Statement: [Rasheed, hasNotableBearer, Rasheed Wallace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rasheed Wallace
Context triple: [Rasheed, hasNotableBearer, Rasheed Wallace]
  • A. Rasheed Wallace chosen
    Rasheed Wallace is a former NBA All-Star power forward known for his versatile scoring, defensive intensity, and fiery on-court demeanor, who won a championship with the Detroit Pistons.
  • B. Ben Wallace
    Ben Wallace is a British Conservative politician who served as the United Kingdom’s Secretary of State for Defence.
  • C. Ben Wallace
    Ben Wallace is a former NBA center renowned for his dominant defense, rebounding, and shot-blocking, serving as a cornerstone of the Detroit Pistons’ early-2000s championship success.
  • D. Grant Hill
    Grant Hill is a former NBA star forward renowned for his all-around versatility, multiple All-Star selections, and a career that spanned teams like the Detroit Pistons and Orlando Magic.
  • E. Grant Hill
    Grant Hill is a film producer best known for his work on acclaimed movies such as "The Thin Red Line," "The Matrix" sequels, and other major Hollywood productions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c687f5fac48190a09e4838d9c6b45d completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b09a6fa88190ba8e454b9ad421a0 completed March 27, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c700755874819083cd0facebd7aa3d completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:02 p.m.