Triple

T13744434
Position Surface form Disambiguated ID Type / Status
Subject Bishop E330175 entity
Predicate hasNotableBearer P458 FINISHED
Object Alison Bishop
Alison Bishop is a computer scientist and cryptographer known for her work in security and privacy as well as for her involvement in stand-up comedy.
E1096945 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: Alison Bishop | Statement: [Bishop, hasNotableBearer, Alison Bishop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alison Bishop
Context triple: [Bishop, hasNotableBearer, Alison Bishop]
  • A. Alison Benson
    Alison Benson is a television producer and executive known for her work overseeing series such as the comedy show "Camping."
  • B. Alison Wright
    Alison Wright is a British actress known for her acclaimed television roles, including standout performances in series such as "The Americans" and "Sneaky Pete."
  • C. Alison Brown
    Alison Brown is a film industry professional best known for her role in founding the American animation company Blue Sky Studios.
  • D. Alison Anderson
    Alison Anderson is an Australian politician and Indigenous leader from the Northern Territory known for her advocacy on Aboriginal rights and community development.
  • E. Alison Woods
    Alison Woods is an American actress best known for her role in the horror-comedy film "Detention."
  • 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: Alison Bishop
Triple: [Bishop, hasNotableBearer, Alison Bishop]
Generated description
Alison Bishop is a computer scientist and cryptographer known for her work in security and privacy as well as for her involvement in stand-up comedy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Alison Bishop
Target entity description: Alison Bishop is a computer scientist and cryptographer known for her work in security and privacy as well as for her involvement in stand-up comedy.
  • A. Alison Benson
    Alison Benson is a television producer and executive known for her work overseeing series such as the comedy show "Camping."
  • B. Alison Wright
    Alison Wright is a British actress known for her acclaimed television roles, including standout performances in series such as "The Americans" and "Sneaky Pete."
  • C. Alison Brown
    Alison Brown is a film industry professional best known for her role in founding the American animation company Blue Sky Studios.
  • D. Alison Anderson
    Alison Anderson is an Australian politician and Indigenous leader from the Northern Territory known for her advocacy on Aboriginal rights and community development.
  • E. Alison Woods
    Alison Woods is an American actress best known for her role in the horror-comedy film "Detention."
  • 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de020855ec8190a60fa1cb761f2e68 completed April 14, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd54f748d481909661deb151da34c1 completed May 8, 2026, 3:13 a.m.
NEDg Description generation batch_69fd56aaf0dc8190b0eaf84822eb15f0 completed May 8, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_69fd5731c9188190bda2958bef87dfe2 completed May 8, 2026, 3:23 a.m.
Created at: April 9, 2026, 10:08 p.m.