Triple

T15035390
Position Surface form Disambiguated ID Type / Status
Subject TV Comic E378465 entity
Predicate featuredCharacter P12208 FINISHED
Object Sooty
Sooty is a popular British glove puppet bear best known for starring in children’s television shows and stage acts featuring magic tricks and slapstick comedy.
E1133511 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: Sooty | Statement: [TV Comic, featuredCharacter, Sooty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sooty
Context triple: [TV Comic, featuredCharacter, Sooty]
  • A. Blacker
    Blacker is a comparative form of the color term "black," indicating a greater degree of darkness or blackness.
  • B. Tigery
    Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
  • C. Blaak
    Blaak is a central transport hub and urban square in Rotterdam, known for its metro and train station near landmarks like the Cube Houses and Markthal.
  • D. Coppins
    Coppins is a historic country house and former royal residence located in Iver, Buckinghamshire, England.
  • E. Syal
    Syal is the surname of Meera Syal, a prominent British-Indian comedian, writer, playwright, and actress known for her work in television, film, and literature.
  • 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: Sooty
Triple: [TV Comic, featuredCharacter, Sooty]
Generated description
Sooty is a popular British glove puppet bear best known for starring in children’s television shows and stage acts featuring magic tricks and slapstick comedy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sooty
Target entity description: Sooty is a popular British glove puppet bear best known for starring in children’s television shows and stage acts featuring magic tricks and slapstick comedy.
  • A. Blacker
    Blacker is a comparative form of the color term "black," indicating a greater degree of darkness or blackness.
  • B. Tigery
    Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
  • C. Blaak
    Blaak is a central transport hub and urban square in Rotterdam, known for its metro and train station near landmarks like the Cube Houses and Markthal.
  • D. Coppins
    Coppins is a historic country house and former royal residence located in Iver, Buckinghamshire, England.
  • E. Syal
    Syal is the surname of Meera Syal, a prominent British-Indian comedian, writer, playwright, and actress known for her work in television, film, and literature.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded82b29948190acda49cbec3f927a completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dddd0208190b2dac7a078de2931 completed May 9, 2026, 2:37 a.m.
NEDg Description generation batch_69fe9f58e39081909be07cda05484fb3 completed May 9, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_69fe9ff62eb081908e170e099c99283b completed May 9, 2026, 2:46 a.m.
Created at: April 10, 2026, 2:59 a.m.