Triple
T6448967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thelma Ritter |
E139814
|
entity |
| Predicate | awardNominationCount |
P51848
|
FINISHED |
| Object | 6 Academy Award nominations for Best Supporting Actress |
—
|
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: 6 Academy Award nominations for Best Supporting Actress | Statement: [Thelma Ritter, awardNominationCount, 6 Academy Award nominations for Best Supporting Actress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardNominationCount Context triple: [Thelma Ritter, awardNominationCount, 6 Academy Award nominations for Best Supporting Actress]
-
A.
academyAwardsNominationsCount
chosen
Indicates the number of times an entity has been nominated for an Academy Award.
-
B.
mostNominationsCount
Indicates the highest number of nominations that any entity in the relevant set has received.
-
C.
numberOfAwards
Indicates the total count of awards that have been received by an entity.
-
D.
tonyNominationsCount
Indicates the number of Tony Award nominations an entity has received.
-
E.
academyAwardNominations
Indicates that an entity has received one or more nominations for an Academy Award (Oscars).
- 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_69c008b301948190a35854e5284dc822 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069b1a61c81908610264c098d25b0 |
completed | March 22, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69c0673b44148190aed70084f0ff4992 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:47 p.m.