Triple

T14614487
Position Surface form Disambiguated ID Type / Status
Subject William Charles Barber E343047 entity
Predicate familyName P18 FINISHED
Object Barber E325104 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: Barber | Statement: [William Charles Barber, familyName, Barber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barber
Context triple: [William Charles Barber, familyName, Barber]
  • A. Barber chosen
    Barber is a common English occupational surname originally given to people who worked as barbers, cutting hair and performing grooming services.
  • B. the Barber
    The Barber is a comedic character from Monty Python’s “The Lumberjack Song,” serving as the narrator who reveals his unexpected dream of becoming a lumberjack.
  • C. The Barber
    The Barber is a comic supporting character in Miguel de Cervantes’ novel "Don Quixote," serving as a practical townsman who often contrasts with the protagonist’s delusions.
  • D. Barber Booth
    Barber Booth is a small hamlet in the Peak District of Derbyshire, England, known for its rural setting and proximity to popular walking routes near Edale.
  • E. Barbera
    Barbera is a dark-skinned Italian wine grape variety known for producing deeply colored, high-acid red wines, especially in the Piedmont region.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb45264988190a1df13e8b54a85bd completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda92110e88190af47b713dd24520b completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:25 a.m.