Triple
T10917707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet Sixteen |
E257866
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Michelle Coulter
Michelle Coulter is an actress best known for her role in the film "Sweet Sixteen."
|
E949516
|
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: Michelle Coulter | Statement: [Sweet Sixteen, stars, Michelle Coulter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michelle Coulter Context triple: [Sweet Sixteen, stars, Michelle Coulter]
-
A.
Lisa Townsend
Lisa Townsend is the elected Police and Crime Commissioner responsible for overseeing policing strategy and accountability in Surrey, England.
-
B.
Shannon Doughton
Shannon Doughton is a musician best known as a principal performer associated with the band Pod.
-
C.
Michelle Hutcherson
Michelle Hutcherson is best known as the mother of American actor Josh Hutcherson, who has supported and accompanied him throughout his entertainment career.
-
D.
Sarah Bolger
Sarah Bolger is an Irish actress known for her roles in films like "In America" and "The Spiderwick Chronicles" and TV series such as "The Tudors" and "Once Upon a Time."
-
E.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
- 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: Michelle Coulter Triple: [Sweet Sixteen, stars, Michelle Coulter]
Generated description
Michelle Coulter is an actress best known for her role in the film "Sweet Sixteen."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michelle Coulter Target entity description: Michelle Coulter is an actress best known for her role in the film "Sweet Sixteen."
-
A.
Lisa Townsend
Lisa Townsend is the elected Police and Crime Commissioner responsible for overseeing policing strategy and accountability in Surrey, England.
-
B.
Shannon Doughton
Shannon Doughton is a musician best known as a principal performer associated with the band Pod.
-
C.
Michelle Hutcherson
Michelle Hutcherson is best known as the mother of American actor Josh Hutcherson, who has supported and accompanied him throughout his entertainment career.
-
D.
Sarah Bolger
Sarah Bolger is an Irish actress known for her roles in films like "In America" and "The Spiderwick Chronicles" and TV series such as "The Tudors" and "Once Upon a Time."
-
E.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7707ebdcc8190b42cafe21c667c82 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f1658e03a8819098ea2ac2f818a61a |
completed | April 29, 2026, 1:57 a.m. |
| NEDg | Description generation | batch_69f16e31ebfc81908255e24b96bf9a99 |
completed | April 29, 2026, 2:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f1a09eae7481908200709ae9721d53 |
completed | April 29, 2026, 6:09 a.m. |
Created at: April 8, 2026, 9:22 p.m.