Triple

T8705438
Position Surface form Disambiguated ID Type / Status
Subject Locus E206635 entity
Predicate hasColumnist P10455 FINISHED
Object Graham Sleight
Graham Sleight is a British critic and editor best known for his work in science fiction and fantasy literature.
E760392 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: Graham Sleight | Statement: [Locus, hasColumnist, Graham Sleight]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graham Sleight
Context triple: [Locus, hasColumnist, Graham Sleight]
  • A. Graham Sharp
    Graham Sharp is an American banjo player, singer, and songwriter best known as a founding member of the bluegrass band Steep Canyon Rangers.
  • B. Graham Crowley
    Graham Crowley is a British painter known for his figurative and landscape works and for his influential role in contemporary British art since the late 20th century.
  • C. Jon Cornish
    Jon Cornish is a former Canadian Football League star running back who became a prominent community leader and chancellor of the University of Calgary.
  • D. Graham Roland
    Graham Roland is an American television writer and producer known for developing and writing action and thriller series, including co-creating the Tom Clancy adaptation "Jack Ryan."
  • E. Graham Walters
    Graham Walters is a film producer best known for his work on the acclaimed Pixar animated feature "Finding Nemo."
  • 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: Graham Sleight
Triple: [Locus, hasColumnist, Graham Sleight]
Generated description
Graham Sleight is a British critic and editor best known for his work in science fiction and fantasy literature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Graham Sleight
Target entity description: Graham Sleight is a British critic and editor best known for his work in science fiction and fantasy literature.
  • A. Graham Sharp
    Graham Sharp is an American banjo player, singer, and songwriter best known as a founding member of the bluegrass band Steep Canyon Rangers.
  • B. Graham Crowley
    Graham Crowley is a British painter known for his figurative and landscape works and for his influential role in contemporary British art since the late 20th century.
  • C. Jon Cornish
    Jon Cornish is a former Canadian Football League star running back who became a prominent community leader and chancellor of the University of Calgary.
  • D. Graham Roland
    Graham Roland is an American television writer and producer known for developing and writing action and thriller series, including co-creating the Tom Clancy adaptation "Jack Ryan."
  • E. Graham Walters
    Graham Walters is a film producer best known for his work on the acclaimed Pixar animated feature "Finding Nemo."
  • 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_69ca835645e881908f00e3c8b51da81d completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58fb43f081909df5d1e31cb1ec04 completed March 31, 2026, 11:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf88cf76888190a0cdab7f30c791c7 completed April 3, 2026, 9:30 a.m.
NEDg Description generation batch_69cf8a3d8e548190911d44ee36875d44 completed April 3, 2026, 9:37 a.m.
NED2 Entity disambiguation (via description) batch_69cf8ae86e1881908a77f660c061bf69 completed April 3, 2026, 9:39 a.m.
Created at: March 30, 2026, 6:34 p.m.