Triple

T1271389
Position Surface form Disambiguated ID Type / Status
Subject Will Scarlet E15716 entity
Predicate alternativeName P39 FINISHED
Object Will Scarlett E15716 NE FINISHED

How this triple was built (2 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 Scarlett | Statement: [Will Scarlet, alternativeName, Will Scarlett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Will Scarlett
Context triple: [Will Scarlet, alternativeName, Will Scarlett]
  • A. Will Scarlet chosen
    Will Scarlet is a legendary member of Robin Hood’s Merry Men, often portrayed as a dashing, hot-headed outlaw skilled with the sword.
  • B. Lennox Cato
    Lennox Cato is a British antiques dealer and television expert best known for his appearances on the BBC’s "Antiques Roadshow."
  • C. Anthony Skingsley
    Anthony Skingsley was a senior Royal Air Force officer who rose to high command during the late 20th century, overseeing key aspects of the UK's air defense.
  • D. Longshanks
    Longshanks is the nickname of King Edward I of England, known for his tall stature, military campaigns in Wales and Scotland, and significant legal and administrative reforms.
  • E. Gawen Lawrie
    Gawen Lawrie was a 17th-century English Quaker and colonial proprietor who played a key role in the early settlement and governance of West Jersey in North America.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ac998b819c8190ad5a4095d31b5cb1 completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:50 p.m.