Triple
T7712289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nebraska |
E174787
|
entity |
| Predicate | notableOscarNominations |
P6104
|
FINISHED |
| Object | Best Picture |
—
|
LITERAL 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: Best Picture | Statement: [Nebraska, notableOscarNominations, Best Picture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableOscarNominations Context triple: [Nebraska, notableOscarNominations, Best Picture]
-
A.
academyAwardNominations
chosen
Indicates that an entity has received one or more nominations for an Academy Award (Oscars).
-
B.
nominatedIn
Indicates that an entity has been formally put forward as a candidate for an award, position, or recognition within a specific event, context, or time period.
-
C.
notableAwardNominationRecipient
Indicates that an entity has been formally nominated to receive a particular notable award.
-
D.
notableMultipleAwardWinnersAlsoWon
Indicates that entities who are notable multiple award winners have also won an additional specified award.
-
E.
tonyNominations
Indicates that an entity has received one or more nominations for a Tony Award.
- 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ebb7448190ae8d47fe0cbb0907 |
completed | March 27, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69c701683dec8190be9861e592aa8ce0 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:04 p.m.