Triple

T13541361
Position Surface form Disambiguated ID Type / Status
Subject Dani Dennison E323392 entity
Predicate associatedWith P37 FINISHED
Object Binx
Binx is the talking black cat and cursed former human from the film "Hocus Pocus" who helps Dani Dennison and her friends battle the Sanderson sisters.
 E1046751 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: Binx | Statement: [Dani Dennison, associatedWith, Binx]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Binx
Context triple: [Dani Dennison, associatedWith, Binx]
  • A. Old Shep
    "Old Shep" is a sentimental country ballad about a boy and his dog that was famously recorded by Elvis Presley early in his career.
  • B. Laika
    Laika was a Soviet space dog who became the first living creature to orbit Earth, marking a pivotal moment in the early Space Race.
  • C. Laika
    Laika is an American stop-motion animation studio renowned for visually distinctive, critically acclaimed films such as Coraline, ParaNorman, and Kubo and the Two Strings.
  • D. Fido
    Fido is a lesser-known companion character associated with the American folk hero Paul Bunyan in tall tales of the lumberjack’s adventures.
  • E. Fido
    Fido is a Canadian mobile phone service provider known for offering wireless plans and devices, primarily targeting value-conscious consumers.
  • 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: Binx
Triple: [Dani Dennison, associatedWith, Binx]
Generated description
Binx is the talking black cat and cursed former human from the film "Hocus Pocus" who helps Dani Dennison and her friends battle the Sanderson sisters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Binx
Target entity description: Binx is the talking black cat and cursed former human from the film "Hocus Pocus" who helps Dani Dennison and her friends battle the Sanderson sisters.
  • A. Old Shep
    "Old Shep" is a sentimental country ballad about a boy and his dog that was famously recorded by Elvis Presley early in his career.
  • B. Laika
    Laika was a Soviet space dog who became the first living creature to orbit Earth, marking a pivotal moment in the early Space Race.
  • C. Laika
    Laika is an American stop-motion animation studio renowned for visually distinctive, critically acclaimed films such as Coraline, ParaNorman, and Kubo and the Two Strings.
  • D. Fido
    Fido is a lesser-known companion character associated with the American folk hero Paul Bunyan in tall tales of the lumberjack’s adventures.
  • E. Fido
    Fido is a Canadian mobile phone service provider known for offering wireless plans and devices, primarily targeting value-conscious consumers.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafd8ba10819098faadcc6adf251e completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d9eaff881909a3cd9e88bb4ec5e completed May 3, 2026, 2:37 p.m.
NEDg Description generation batch_69f75e7d8970819092116ae7a769ac21 completed May 3, 2026, 2:41 p.m.
NED2 Entity disambiguation (via description) batch_69f75f35c6008190b88e14feddb93a1d completed May 3, 2026, 2:44 p.m.
Created at: April 9, 2026, 9:45 p.m.