Triple

T3884055
Position Surface form Disambiguated ID Type / Status
Subject Bus Stop E92895 entity
Predicate character P662 FINISHED
Object Cherie
Cherie is the naive yet determined young woman who becomes the romantic focus of the cowboy in the classic stage play and film "Bus Stop."
E394416 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: Cherie | Statement: [Bus Stop, character, Cherie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cherie
Context triple: [Bus Stop, character, Cherie]
  • A. Charlene
    Charlene is a feminine given name derived from the male name Charles.
  • B. Felicia
    Felicia is a feminine given name of Latin origin meaning "happy" or "fortunate," used in various cultures around the world.
  • C. Madelaine
    Madelaine is a character in the Danish crime thriller film "The Salvation."
  • D. Bridgette
    Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
  • E. Joanne
    Joanne is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
  • 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: Cherie
Triple: [Bus Stop, character, Cherie]
Generated description
Cherie is the naive yet determined young woman who becomes the romantic focus of the cowboy in the classic stage play and film "Bus Stop."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cherie
Target entity description: Cherie is the naive yet determined young woman who becomes the romantic focus of the cowboy in the classic stage play and film "Bus Stop."
  • A. Charlene
    Charlene is a feminine given name derived from the male name Charles.
  • B. Felicia
    Felicia is a feminine given name of Latin origin meaning "happy" or "fortunate," used in various cultures around the world.
  • C. Madelaine
    Madelaine is a character in the Danish crime thriller film "The Salvation."
  • D. Bridgette
    Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
  • E. Joanne
    Joanne is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
  • 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeec9029908190a7b36a3827734db1 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5125bee048190ba7553797e9fd254 completed March 14, 2026, 7:46 a.m.
NEDg Description generation batch_69b512e3721c8190accd26499191c153 completed March 14, 2026, 7:48 a.m.
NED2 Entity disambiguation (via description) batch_69b513618b888190acda94dcc91d24d2 completed March 14, 2026, 7:50 a.m.
Created at: March 9, 2026, 3:20 p.m.