Triple

T3994697
Position Surface form Disambiguated ID Type / Status
Subject Blansky's Beauties E87071 entity
Predicate character P662 FINISHED
Object Cindy
Cindy is a fictional character from the short-lived 1970s American sitcom "Blansky's Beauties," which followed the lives of Las Vegas showgirls.
 E403599 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: Cindy | Statement: [Blansky's Beauties, character, Cindy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cindy
Context triple: [Blansky's Beauties, character, Cindy]
  • A. Cynthia
    Cynthia is a common feminine given name used in various cultures, often associated with the Greek moon goddess Artemis.
  • B. Candice
    Candice is a feminine given name commonly used in English-speaking countries, often associated with the meaning "clarity" or "purity."
  • C. Cindy Birdsong
    Cindy Birdsong is an American singer best known as a member of the Motown girl group The Supremes, with whom she achieved major success in the late 1960s and 1970s.
  • D. Tina
    Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
  • E. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • 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: Cindy
Triple: [Blansky's Beauties, character, Cindy]
Generated description
Cindy is a fictional character from the short-lived 1970s American sitcom "Blansky's Beauties," which followed the lives of Las Vegas showgirls.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cindy
Target entity description: Cindy is a fictional character from the short-lived 1970s American sitcom "Blansky's Beauties," which followed the lives of Las Vegas showgirls.
  • A. Cynthia
    Cynthia is a common feminine given name used in various cultures, often associated with the Greek moon goddess Artemis.
  • B. Candice
    Candice is a feminine given name commonly used in English-speaking countries, often associated with the meaning "clarity" or "purity."
  • C. Cindy Birdsong
    Cindy Birdsong is an American singer best known as a member of the Motown girl group The Supremes, with whom she achieved major success in the late 1960s and 1970s.
  • D. Tina
    Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
  • E. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • 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_69aed94118148190975e6aa4e554cde9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa1f0fb88190aafbfdc98bc8652d completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5403c703081908070625ebfb6fb5f completed March 14, 2026, 11:02 a.m.
NEDg Description generation batch_69b540ec36a4819082a9cbefc99bd683 completed March 14, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69b5416d182c81908b1ae43ed097d288 completed March 14, 2026, 11:07 a.m.
Created at: March 9, 2026, 3:34 p.m.