Triple

T1271390
Position Surface form Disambiguated ID Type / Status
Subject Will Scarlet E15716 entity
Predicate alternativeName P39 FINISHED
Object Will Scathelock
Will Scathelock is a legendary member of Robin Hood’s band of outlaws, better known in popular folklore as Will Scarlet.
E167379 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: Will Scathelock | Statement: [Will Scarlet, alternativeName, Will Scathelock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Will Scathelock
Context triple: [Will Scarlet, alternativeName, Will Scathelock]
  • A. Michael Sexton
    Michael Sexton is an American businessman best known for co-founding and running the controversial real estate training venture Trump University alongside Donald Trump.
  • B. Jack Driscoll
    Jack Driscoll is a central heroic character in the 1933 film "King Kong," serving as the ship's first mate and the primary human protagonist who helps rescue Ann Darrow from the giant ape.
  • C. Sam Wheeler
    Sam Wheeler is the father of Ted Wheeler, the mayor of Portland, Oregon.
  • D. Sean Kilpatrick
    Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
  • E. Jarvis Hunt
    Jarvis Hunt was a prominent American architect known for designing significant railroad stations and public buildings in the late 19th and early 20th centuries.
  • 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: Will Scathelock
Triple: [Will Scarlet, alternativeName, Will Scathelock]
Generated description
Will Scathelock is a legendary member of Robin Hood’s band of outlaws, better known in popular folklore as Will Scarlet.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Will Scathelock
Target entity description: Will Scathelock is a legendary member of Robin Hood’s band of outlaws, better known in popular folklore as Will Scarlet.
  • A. Michael Sexton
    Michael Sexton is an American businessman best known for co-founding and running the controversial real estate training venture Trump University alongside Donald Trump.
  • B. Jack Driscoll
    Jack Driscoll is a central heroic character in the 1933 film "King Kong," serving as the ship's first mate and the primary human protagonist who helps rescue Ann Darrow from the giant ape.
  • C. Sam Wheeler
    Sam Wheeler is the father of Ted Wheeler, the mayor of Portland, Oregon.
  • D. Sean Kilpatrick
    Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
  • E. Jarvis Hunt
    Jarvis Hunt was a prominent American architect known for designing significant railroad stations and public buildings in the late 19th and early 20th centuries.
  • 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_69a4935a94308190bb92555b79032824 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4c06ae7b88190a1e0b5232d84a7b1 completed March 1, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e6027448190b10c65bcafe9fedf completed March 8, 2026, 5:51 a.m.
NEDg Description generation batch_69ad100fc7108190bf5211fb5817ca5f completed March 8, 2026, 5:58 a.m.
NED2 Entity disambiguation (via description) batch_69ad105a9bcc8190ba6d14df99ff2a7a completed March 8, 2026, 5:59 a.m.
Created at: March 1, 2026, 7:50 p.m.