Triple

T10323233
Position Surface form Disambiguated ID Type / Status
Subject Suzie Gold E242691 entity
Predicate starring P1507 FINISHED
Object Stanley Townsend
Stanley Townsend is an Irish character actor known for his extensive work in film, television, and theatre, often portraying complex supporting roles.
 E882937 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: Stanley Townsend | Statement: [Suzie Gold, starring, Stanley Townsend]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stanley Townsend
Context triple: [Suzie Gold, starring, Stanley Townsend]
  • A. Stanley Arnold
    Stanley Arnold is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Arnold.
  • B. George Stanley
    George Stanley was a Canadian-born poet and educator associated with the San Francisco Renaissance literary movement.
  • C. George Stanley
    George Stanley was an American sculptor best known for designing the iconic Oscar statuette for the Academy Awards.
  • D. Stanley Ralph
    Stanley Ralph is the son of American actress and singer Sheryl Lee Ralph.
  • E. Stanley Anderson
    Stanley Anderson was an American character actor known for his numerous supporting roles in film and television, often portraying authoritative figures such as judges, generals, and politicians.
  • 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: Stanley Townsend
Triple: [Suzie Gold, starring, Stanley Townsend]
Generated description
Stanley Townsend is an Irish character actor known for his extensive work in film, television, and theatre, often portraying complex supporting roles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stanley Townsend
Target entity description: Stanley Townsend is an Irish character actor known for his extensive work in film, television, and theatre, often portraying complex supporting roles.
  • A. Stanley Arnold
    Stanley Arnold is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Arnold.
  • B. George Stanley
    George Stanley was a Canadian-born poet and educator associated with the San Francisco Renaissance literary movement.
  • C. George Stanley
    George Stanley was an American sculptor best known for designing the iconic Oscar statuette for the Academy Awards.
  • D. Stanley Ralph
    Stanley Ralph is the son of American actress and singer Sheryl Lee Ralph.
  • E. Stanley Anderson
    Stanley Anderson was an American character actor known for his numerous supporting roles in film and television, often portraying authoritative figures such as judges, generals, and politicians.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d6cdb6cc8190b37ca4494287128b completed April 7, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69de21d85ee08190adfab9926fea1709 completed April 14, 2026, 11:15 a.m.
NEDg Description generation batch_69de25d25474819081402b75ef7492f6 completed April 14, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_69de2808244c8190bdb2d4d49f30e0d7 completed April 14, 2026, 11:42 a.m.
Created at: April 6, 2026, 11:50 a.m.