Triple

T18506334
Position Surface form Disambiguated ID Type / Status
Subject WNYC Studios E452206 entity
Predicate produces P490 FINISHED
Object Nancy
Nancy is a podcast from WNYC Studios that explores LGBTQ+ stories, identities, and experiences through personal narratives and conversations.
 E1329764 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: Nancy | Statement: [WNYC Studios, produces, Nancy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nancy
Context triple: [WNYC Studios, produces, Nancy]
  • A. Nancy
    Nancy is a central character in the meta-horror comedy film "The Final Girls," portrayed as a sweet but archetypal 1980s slasher-movie camp counselor who becomes crucial to the story’s emotional core.
  • B. Nancy
    Nancy is a key child character in the Doctor Who episode "The Doctor Dances," known for leading a group of homeless children during the London Blitz.
  • C. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • D. Nancy
    Nancy is a historic city in northeastern France renowned for its elegant 18th-century architecture and UNESCO-listed Place Stanislas.
  • E. Nancy
    Nancy is a household servant character associated with Gregory Anton, likely appearing in the same narrative or dramatic work as part of his domestic staff.
  • 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: Nancy
Triple: [WNYC Studios, produces, Nancy]
Generated description
Nancy is a podcast from WNYC Studios that explores LGBTQ+ stories, identities, and experiences through personal narratives and conversations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nancy
Target entity description: Nancy is a podcast from WNYC Studios that explores LGBTQ+ stories, identities, and experiences through personal narratives and conversations.
  • A. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • B. Nancy
    Nancy is a historic city in northeastern France renowned for its elegant 18th-century architecture and UNESCO-listed Place Stanislas.
  • C. Nancy
    Nancy is a key child character in the Doctor Who episode "The Doctor Dances," known for leading a group of homeless children during the London Blitz.
  • D. Nancy
    Nancy is a household servant character associated with Gregory Anton, likely appearing in the same narrative or dramatic work as part of his domestic staff.
  • E. Nancy
    Nancy is a central character in the meta-horror comedy film "The Final Girls," portrayed as a sweet but archetypal 1980s slasher-movie camp counselor who becomes crucial to the story’s emotional core.
  • 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_69d8d386df84819092355ebb260d848e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5334266708190b59aca3a2218c095 completed April 19, 2026, 7:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0491672dc08190a09c74cb4e6cf06a completed May 13, 2026, 2:57 p.m.
NEDg Description generation batch_6a04966f7b488190881d28e858ed7908 completed May 13, 2026, 3:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0496ec05608190bfd16a0a36735255 completed May 13, 2026, 3:21 p.m.
Created at: April 10, 2026, 11:36 a.m.