Triple

T3932893
Position Surface form Disambiguated ID Type / Status
Subject Kevin Love E90835 entity
Predicate relative P37 FINISHED
Object Stan Love
Stan Love is a former American professional basketball player who played in the NBA during the 1970s.
E399611 NE FINISHED

How this triple was built (4 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: Stan Love | Statement: [Kevin Love, relative, Stan Love]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stan Love
Context triple: [Kevin Love, relative, Stan Love]
  • A. Doug Laird
    Doug Laird is a technology entrepreneur best known as one of the founders of the innovative microprocessor company Transmeta.
  • B. David Loughery
    David Loughery is an American screenwriter and producer known for writing thrillers and genre films such as "Passenger 57," "Lakeview Terrace," and "Obsessed."
  • C. Kirk Wise
    Kirk Wise is an American film director, screenwriter, and animator best known for co-directing acclaimed Disney animated features such as "Beauty and the Beast" and "The Hunchback of Notre Dame."
  • D. Jim Reardon
    Jim Reardon is an American animation writer and director best known for his work on The Simpsons and for co-writing the screenplay for Disney’s Zootopia.
  • E. Ed Vargo
    Ed Vargo was a prominent Major League Baseball umpire who worked in the National League for over two decades and officiated multiple World Series and All-Star Games.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Stan Love
Triple: [Kevin Love, relative, Stan Love]
Generated description
Stan Love is a former American professional basketball player who played in the NBA during the 1970s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stan Love
Target entity description: Stan Love is a former American professional basketball player who played in the NBA during the 1970s.
  • A. Doug Laird
    Doug Laird is a technology entrepreneur best known as one of the founders of the innovative microprocessor company Transmeta.
  • B. David Loughery
    David Loughery is an American screenwriter and producer known for writing thrillers and genre films such as "Passenger 57," "Lakeview Terrace," and "Obsessed."
  • C. Kirk Wise
    Kirk Wise is an American film director, screenwriter, and animator best known for co-directing acclaimed Disney animated features such as "Beauty and the Beast" and "The Hunchback of Notre Dame."
  • D. Jim Reardon
    Jim Reardon is an American animation writer and director best known for his work on The Simpsons and for co-writing the screenplay for Disney’s Zootopia.
  • E. Ed Vargo
    Ed Vargo was a prominent Major League Baseball umpire who worked in the National League for over two decades and officiated multiple World Series and All-Star Games.
  • F. None of above. chosen

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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedaaf3c881909539831bf3a8bf10 completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52887d4a48190b51df3f51ff197c0 completed March 14, 2026, 9:21 a.m.
NEDg Description generation batch_69b529a1486881908ff348558199232b completed March 14, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_69b52a43c6f081908366d9848728f98a completed March 14, 2026, 9:28 a.m.
Created at: March 9, 2026, 3:23 p.m.