Triple
T14400246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doc Hollywood |
E357050
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Susan Solt
Susan Solt is a film producer best known for her work on the 1991 romantic comedy "Doc Hollywood."
|
E1098544
|
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: Susan Solt | Statement: [Doc Hollywood, producer, Susan Solt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susan Solt Context triple: [Doc Hollywood, producer, Susan Solt]
-
A.
Suzanne Scott
Suzanne Scott is an individual honored as a namesake of the Suzanne and Walter Scott Aquarium, indicating her significant personal or philanthropic connection to that institution.
-
B.
Carol Ann Susi
Carol Ann Susi was an American character actress best known for voicing the unseen Mrs. Wolowitz on the television series "The Big Bang Theory."
-
C.
Suzanne Todd
Suzanne Todd is an American film producer known for her work on influential movies such as "Memento" and the "Austin Powers" series.
-
D.
Sue Brown
Sue Brown is a spirited and charming young woman in P. G. Wodehouse’s Blandings Castle stories, notably involved in romantic and comedic entanglements.
-
E.
Carol Seaver
Carol Seaver is the intelligent, ambitious, and sometimes neurotic teenage daughter in the family sitcom "Growing Pains."
- 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: Susan Solt Triple: [Doc Hollywood, producer, Susan Solt]
Generated description
Susan Solt is a film producer best known for her work on the 1991 romantic comedy "Doc Hollywood."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Susan Solt Target entity description: Susan Solt is a film producer best known for her work on the 1991 romantic comedy "Doc Hollywood."
-
A.
Suzanne Scott
Suzanne Scott is an individual honored as a namesake of the Suzanne and Walter Scott Aquarium, indicating her significant personal or philanthropic connection to that institution.
-
B.
Carol Ann Susi
Carol Ann Susi was an American character actress best known for voicing the unseen Mrs. Wolowitz on the television series "The Big Bang Theory."
-
C.
Suzanne Todd
Suzanne Todd is an American film producer known for her work on influential movies such as "Memento" and the "Austin Powers" series.
-
D.
Sue Brown
Sue Brown is a spirited and charming young woman in P. G. Wodehouse’s Blandings Castle stories, notably involved in romantic and comedic entanglements.
-
E.
Carol Seaver
Carol Seaver is the intelligent, ambitious, and sometimes neurotic teenage daughter in the family sitcom "Growing Pains."
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de908500048190bb6a20fe318d5c62 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bc424f88190ab3a1c1aec61cb40 |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5cf4dedc81908988f13f0fc9f510 |
completed | May 8, 2026, 3:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5dcf151c8190959b3240813a1d71 |
completed | May 8, 2026, 3:51 a.m. |
Created at: April 10, 2026, 1:17 a.m.