Triple

T21449042
Position Surface form Disambiguated ID Type / Status
Subject Walt Kowalski E529157 entity
Predicate hasNeighbor P5707 FINISHED
Object Sue Lor
Sue Lor is a Hmong American teenager who becomes Walt Kowalski’s young neighbor and friend in the film "Gran Torino."
 E1489122 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: Sue Lor | Statement: [Walt Kowalski, hasNeighbor, Sue Lor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sue Lor
Context triple: [Walt Kowalski, hasNeighbor, Sue Lor]
  • A. Sue Seeary
    Sue Seeary is a television producer best known for serving as an executive producer on the Australian crime drama series NCIS: Sydney.
  • B. Sue Roderick
    Sue Roderick is an actress known for her role in the film "Twin Town."
  • C. Sue Lloyd
    Sue Lloyd was a British actress best known for her roles in 1960s film and television, including the spy thriller "The Ipcress File" and the TV series "The Baron."
  • D. Sue Gunter
    Sue Gunter was a Hall of Fame American women’s basketball coach best known for her long, successful tenure leading major collegiate programs and elevating the profile of the women’s game.
  • E. Sue Naegle
    Sue Naegle is an American television executive and producer best known for her tenure as president of HBO Entertainment and for founding the production company Naegle Ink.
  • 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: Sue Lor
Triple: [Walt Kowalski, hasNeighbor, Sue Lor]
Generated description
Sue Lor is a Hmong American teenager who becomes Walt Kowalski’s young neighbor and friend in the film "Gran Torino."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sue Lor
Target entity description: Sue Lor is a Hmong American teenager who becomes Walt Kowalski’s young neighbor and friend in the film "Gran Torino."
  • A. Sue Seeary
    Sue Seeary is a television producer best known for serving as an executive producer on the Australian crime drama series NCIS: Sydney.
  • B. Sue Roderick
    Sue Roderick is an actress known for her role in the film "Twin Town."
  • C. Sue Lloyd
    Sue Lloyd was a British actress best known for her roles in 1960s film and television, including the spy thriller "The Ipcress File" and the TV series "The Baron."
  • D. Sue Gunter
    Sue Gunter was a Hall of Fame American women’s basketball coach best known for her long, successful tenure leading major collegiate programs and elevating the profile of the women’s game.
  • E. Sue Naegle
    Sue Naegle is an American television executive and producer best known for her tenure as president of HBO Entertainment and for founding the production company Naegle Ink.
  • 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_69e0c457579481909db68053ed99750c completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9d11ca48190aafe25c97dfa5578 completed April 23, 2026, 9:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09e8167d6081908b68ca932c184894 completed May 17, 2026, 4:08 p.m.
NEDg Description generation batch_6a09e8d6d1a88190b3f48111ed6a4043 completed May 17, 2026, 4:12 p.m.
NED2 Entity disambiguation (via description) batch_6a09e94d6f2c819097df5c0a2b59e63a completed May 17, 2026, 4:14 p.m.
Created at: April 16, 2026, 6:06 p.m.