Triple
T10198250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 88th Academy Awards |
E238817
|
entity |
| Predicate | producerOfBestPicture |
P89576
|
FINISHED |
| Object | Nicole Rocklin |
E822921
|
NE FINISHED |
How this triple was built (2 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: Nicole Rocklin | Statement: [88th Academy Awards, producerOfBestPicture, Nicole Rocklin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicole Rocklin Context triple: [88th Academy Awards, producerOfBestPicture, Nicole Rocklin]
-
A.
Nicole Rocklin
chosen
Nicole Rocklin is an American film producer best known for co-producing the Academy Award–winning investigative drama "Spotlight."
-
B.
Michelle Mylett
Michelle Mylett is a Canadian actress best known for playing Katy on the comedy series "Letterkenny."
-
C.
Nicole P. Stott
Nicole P. Stott is an American engineer, retired NASA astronaut, and aquanaut known for her long-duration stay on the International Space Station and her work combining space exploration with art and education.
-
D.
Amanda Detmer
Amanda Detmer is an American actress known for her roles in early 2000s films and television series, often appearing in comedies and romantic comedies.
-
E.
Amanda Askell
Amanda Askell is an AI researcher and ethicist known for her work on AI alignment and safety, including contributions at OpenAI.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca84e1ea088190b38162e43d4cfa8f |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdee3c44408190b09fa41f2d257c04 |
completed | April 2, 2026, 4:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a7e63c588190b239f8bdb13a3f3c |
completed | April 8, 2026, 7:09 p.m. |
Created at: March 30, 2026, 9:14 p.m.