Triple
T22946479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 10th Academy Awards |
E569886
|
entity |
| Predicate | bestSoundRecordingRecipient |
P37207
|
FINISHED |
| Object | Thomas T. Moulton |
—
|
NE NERFINISHED |
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: Thomas T. Moulton | Statement: [10th Academy Awards, bestSoundRecordingRecipient, Thomas T. Moulton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestSoundRecordingRecipient Context triple: [10th Academy Awards, bestSoundRecordingRecipient, Thomas T. Moulton]
-
A.
bestSoundRecordingWinner
chosen
Indicates that one entity is the winner of an award for best sound recording in relation to another entity (such as a work, event, or year).
-
B.
soundRecordingNominee
Indicates that an entity is nominated for an award specifically recognizing a sound recording.
-
C.
bestSoundEditingWinner
Indicates that the subject is the winner of an award for best sound editing in a given context or event.
-
D.
recordingOf
Indicates that one entity is an audio or video capture or performance that documents, represents, or preserves another entity (such as a work, event, or expression).
-
E.
bestSoundMixingWinner
Indicates that the subject is the winner of an award or recognition for best sound mixing.
- F. None of above.
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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1819d2d7881909e6390717ff79df0 |
completed | April 29, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:46 p.m.