Triple
T22091428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'd Do Anything |
E545922
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Suzy Lamb
Suzy Lamb is a British television producer known for her work on major entertainment and talent competition shows.
|
E1519111
|
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: Suzy Lamb | Statement: [I'd Do Anything, executiveProducer, Suzy Lamb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suzy Lamb Context triple: [I'd Do Anything, executiveProducer, Suzy Lamb]
-
A.
Suzy Bishop
Suzy Bishop is a lonely, sharp-witted adolescent girl who runs away from home with a boy scout in Wes Anderson’s film "Moonrise Kingdom."
-
B.
Susie Brown
Susie Brown is a fictional character portrayed by Viola Davis, likely serving as a significant supporting figure in the story she appears in.
-
C.
Susie Sprague
Susie Sprague is an American model and actress best known for her work in glamour modeling and for her high-profile marriage to actor Corey Feldman.
-
D.
Susie Lewis
Susie Lewis is an animator and producer best known for her work on the MTV animated series "Daria."
-
E.
Susie Bannion
Susie Bannion is the young American dancer who becomes entangled with a coven of witches at a prestigious Berlin dance academy in the 2018 horror film "Suspiria."
- 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: Suzy Lamb Triple: [I'd Do Anything, executiveProducer, Suzy Lamb]
Generated description
Suzy Lamb is a British television producer known for her work on major entertainment and talent competition shows.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suzy Lamb Target entity description: Suzy Lamb is a British television producer known for her work on major entertainment and talent competition shows.
-
A.
Suzy Bishop
Suzy Bishop is a lonely, sharp-witted adolescent girl who runs away from home with a boy scout in Wes Anderson’s film "Moonrise Kingdom."
-
B.
Susie Brown
Susie Brown is a fictional character portrayed by Viola Davis, likely serving as a significant supporting figure in the story she appears in.
-
C.
Susie Sprague
Susie Sprague is an American model and actress best known for her work in glamour modeling and for her high-profile marriage to actor Corey Feldman.
-
D.
Susie Lewis
Susie Lewis is an animator and producer best known for her work on the MTV animated series "Daria."
-
E.
Susie Bannion
Susie Bannion is the young American dancer who becomes entangled with a coven of witches at a prestigious Berlin dance academy in the 2018 horror film "Suspiria."
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e5edf08190a6743955bc872417 |
completed | April 28, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a879b9130819089f8e2b7106f875b |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a891eb0708190a4575a01f45b98aa |
completed | May 18, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a89977c8c8190a5c87d1c2b68ed48 |
completed | May 18, 2026, 3:37 a.m. |
Created at: April 16, 2026, 8:29 p.m.