Triple

T1770953
Position Surface form Disambiguated ID Type / Status
Subject Wonder Woman (2017 film) E38872 entity
Predicate producer P490 FINISHED
Object Richard Suckle
Richard Suckle is an American film producer known for his work on major studio projects, including the DC superhero film "Wonder Woman" (2017).
 E302399 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: Richard Suckle | Statement: [Wonder Woman (2017 film), producer, Richard Suckle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Richard Suckle
Context triple: [Wonder Woman (2017 film), producer, Richard Suckle]
  • A. Richard Hiscott
    Richard Hiscott is an editor known for his work on the television series "Willow."
  • B. Richard Bristow
    Richard Bristow was a 16th-century English Catholic scholar and theologian who contributed to the development and annotation of the Douay–Rheims Bible.
  • C. Richard Laxton
    Richard Laxton is a British film and television director known for his work on dramas such as the period film "Effie Gray."
  • D. Richard Sibson
    Richard Sibson is a distinguished geologist recognized for his influential work on fault mechanics and earthquake processes.
  • E. William Rimmer
    William Rimmer was a 19th-century British-born American artist, sculptor, and influential art teacher known for his anatomically precise and imaginative figure studies.
  • 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: Richard Suckle
Triple: [Wonder Woman (2017 film), producer, Richard Suckle]
Generated description
Richard Suckle is an American film producer known for his work on major studio projects, including the DC superhero film "Wonder Woman" (2017).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Richard Suckle
Target entity description: Richard Suckle is an American film producer known for his work on major studio projects, including the DC superhero film "Wonder Woman" (2017).
  • A. Richard Hiscott
    Richard Hiscott is an editor known for his work on the television series "Willow."
  • B. Richard Bristow
    Richard Bristow was a 16th-century English Catholic scholar and theologian who contributed to the development and annotation of the Douay–Rheims Bible.
  • C. Richard Laxton
    Richard Laxton is a British film and television director known for his work on dramas such as the period film "Effie Gray."
  • D. Richard Sibson
    Richard Sibson is a distinguished geologist recognized for his influential work on fault mechanics and earthquake processes.
  • E. William Rimmer
    William Rimmer was a 19th-century British-born American artist, sculptor, and influential art teacher known for his anatomically precise and imaginative figure studies.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa648fe908819098fd27b74b17fabb completed March 6, 2026, 5:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce7154648190aa55d54ca5e50559 completed March 10, 2026, 7:55 a.m.
NEDg Description generation batch_69afd22a81dc8190809f94f8e49ddad8 completed March 10, 2026, 8:11 a.m.
NED2 Entity disambiguation (via description) batch_69afd3b8daec81908c5d507e35ba997e completed March 10, 2026, 8:18 a.m.
Created at: March 4, 2026, 7:31 p.m.