Triple

T3040538
Position Surface form Disambiguated ID Type / Status
Subject Julia Sweeney E83115 entity
Predicate notableWork P4 FINISHED
Object It’s Pat
"It’s Pat" is a recurring Saturday Night Live sketch and 1994 comedy film centered on an androgynous character whose ambiguous gender is the source of ongoing humorous confusion.
E320308 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: It’s Pat | Statement: [Julia Sweeney, notableWork, It’s Pat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: It’s Pat
Context triple: [Julia Sweeney, notableWork, It’s Pat]
  • A. Pat
    Pat is the commonly used short form of the given name Patrick, often used as a casual or familiar nickname.
  • B. Patpatar
    Patpatar is an Austronesian language spoken in parts of New Ireland in Papua New Guinea, belonging to the Meso-Melanesian subgroup.
  • C. Pat and Mike
    Pat and Mike is a 1952 sports comedy film starring Katharine Hepburn and Spencer Tracy, known for its witty script and depiction of a female athlete challenging gender norms.
  • D. Pete
    Pete is a common masculine given name, typically used as a familiar or informal form of the name Peter.
  • E. Pete
    Pete is a classic Disney cartoon villain, best known as Mickey Mouse’s burly, antagonistic foe in the Mickey Mouse franchise.
  • 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: It’s Pat
Triple: [Julia Sweeney, notableWork, It’s Pat]
Generated description
"It’s Pat" is a recurring Saturday Night Live sketch and 1994 comedy film centered on an androgynous character whose ambiguous gender is the source of ongoing humorous confusion.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: It’s Pat
Target entity description: "It’s Pat" is a recurring Saturday Night Live sketch and 1994 comedy film centered on an androgynous character whose ambiguous gender is the source of ongoing humorous confusion.
  • A. Pat
    Pat is the commonly used short form of the given name Patrick, often used as a casual or familiar nickname.
  • B. Patpatar
    Patpatar is an Austronesian language spoken in parts of New Ireland in Papua New Guinea, belonging to the Meso-Melanesian subgroup.
  • C. Pat and Mike
    Pat and Mike is a 1952 sports comedy film starring Katharine Hepburn and Spencer Tracy, known for its witty script and depiction of a female athlete challenging gender norms.
  • D. Pete
    Pete is the nickname of Grover Cleveland Alexander, a Hall of Fame Major League Baseball pitcher and one of the greatest hurlers of the early 20th century.
  • E. Pete
    Pete is a common masculine given name, typically used as a familiar or informal form of the name Peter.
  • 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_69ad8b2298908190a7cb4e9bdbf064d0 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b59fea8819091796e30812df9c5 completed March 8, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ded01a1481908be7d44c2bf4e638 completed March 11, 2026, 9:29 p.m.
NEDg Description generation batch_69b1df61bb208190b7714ff14ff81a99 completed March 11, 2026, 9:32 p.m.
NED2 Entity disambiguation (via description) batch_69b1dfd8fc5481908f1e130226d606fb completed March 11, 2026, 9:34 p.m.
Created at: March 8, 2026, 3:01 p.m.