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.