Triple
T13222208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Animal Practice |
E314781
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Betsy Sodaro
Betsy Sodaro is an American comedian and character actress known for her high-energy performances in television comedies and improv.
|
E1123907
|
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: Betsy Sodaro | Statement: [Animal Practice, castMember, Betsy Sodaro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Betsy Sodaro Context triple: [Animal Practice, castMember, Betsy Sodaro]
-
A.
Vicki Sirotta
Vicki Sirotta is a film producer best known for her work on the horror-thriller movie "The Prophecy."
-
B.
Laura Rister
Laura Rister is a film producer and executive known for her work on independent and prestige projects, including the financial thriller "Margin Call."
-
C.
Betsy Koch
Betsy Koch is a film producer known for her work on the darkly comedic horror-thriller "The Menu."
-
D.
Laura Bickford
Laura Bickford is an American film producer best known for her work on acclaimed independent and studio films, including the Oscar-winning drama "Traffic."
-
E.
Betsy Gaghan
Betsy Gaghan is the daughter of American screenwriter and director Stephen Gaghan.
- 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: Betsy Sodaro Triple: [Animal Practice, castMember, Betsy Sodaro]
Generated description
Betsy Sodaro is an American comedian and character actress known for her high-energy performances in television comedies and improv.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Betsy Sodaro Target entity description: Betsy Sodaro is an American comedian and character actress known for her high-energy performances in television comedies and improv.
-
A.
Vicki Sirotta
Vicki Sirotta is a film producer best known for her work on the horror-thriller movie "The Prophecy."
-
B.
Laura Rister
Laura Rister is a film producer and executive known for her work on independent and prestige projects, including the financial thriller "Margin Call."
-
C.
Betsy Koch
Betsy Koch is a film producer known for her work on the darkly comedic horror-thriller "The Menu."
-
D.
Laura Bickford
Laura Bickford is an American film producer best known for her work on acclaimed independent and studio films, including the Oscar-winning drama "Traffic."
-
E.
Betsy Gaghan
Betsy Gaghan is the daughter of American screenwriter and director Stephen Gaghan.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf74d708190a61d8ad938653b06 |
completed | April 10, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64e2991c81908f474fe07a6ba10a |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe674ad60c8190a3be185f71983b2f |
completed | May 8, 2026, 10:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe67a5c7ec8190b30f190e9416a41c |
completed | May 8, 2026, 10:45 p.m. |
Created at: April 9, 2026, 9:18 p.m.