Triple

T14225932
Position Surface form Disambiguated ID Type / Status
Subject Betty Comden E352617 entity
Predicate notableWork P4 FINISHED
Object Say, Darling
Say, Darling is a 1958 Broadway musical comedy, based on a novel by Richard Bissell, that satirizes the behind-the-scenes creation of a stage show.
E1087250 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: Say, Darling | Statement: [Betty Comden, notableWork, Say, Darling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Say, Darling
Context triple: [Betty Comden, notableWork, Say, Darling]
  • A. Listen, Darling
    Listen, Darling is a 1938 American musical comedy film best known for featuring a young Judy Garland in an early starring role.
  • B. Darling
    Darling is a residential suburb in Melbourne, Victoria, known for its local train station on the Glen Waverley railway line and its proximity to the city.
  • C. Darling
    Darling is a surname most prominently associated with Ron Darling, a former Major League Baseball pitcher and current television baseball analyst.
  • D. Darling
    Darling is the kind, affectionate human owner of Lady in Disney's animated film "Lady and the Tramp."
  • E. Darling
    Darling is a character played by Eiza González in the action film "Baby Driver," known as a stylish and dangerous bank robber and the girlfriend of fellow criminal Buddy.
  • 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: Say, Darling
Triple: [Betty Comden, notableWork, Say, Darling]
Generated description
Say, Darling is a 1958 Broadway musical comedy, based on a novel by Richard Bissell, that satirizes the behind-the-scenes creation of a stage show.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Say, Darling
Target entity description: Say, Darling is a 1958 Broadway musical comedy, based on a novel by Richard Bissell, that satirizes the behind-the-scenes creation of a stage show.
  • A. Listen, Darling
    Listen, Darling is a 1938 American musical comedy film best known for featuring a young Judy Garland in an early starring role.
  • B. Darling
    Darling is a residential suburb in Melbourne, Victoria, known for its local train station on the Glen Waverley railway line and its proximity to the city.
  • C. Darling
    Darling is a surname most prominently associated with Ron Darling, a former Major League Baseball pitcher and current television baseball analyst.
  • D. Darling
    Darling is the kind, affectionate human owner of Lady in Disney's animated film "Lady and the Tramp."
  • E. Darling
    "Darling" is a 2010 Telugu romantic comedy film starring Prabhas, known for its lighthearted love story and popular music.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6228e53c8190abbe4e2d88a7362a completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd281611b48190b787e38ba9c733a4 completed May 8, 2026, 12:02 a.m.
NEDg Description generation batch_69fd2a5c80308190868967a402c5fa42 completed May 8, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_69fd2af4ddf8819089435b849415b941 completed May 8, 2026, 12:14 a.m.
Created at: April 10, 2026, 1:06 a.m.