Triple
T15019617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Globe for I Never Promised You a Rose Garden |
E378048
|
entity |
| Predicate | awardForGenre |
P56334
|
FINISHED |
| Object | dramatic cinema |
—
|
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: dramatic cinema | Statement: [Golden Globe for I Never Promised You a Rose Garden, awardForGenre, dramatic cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardForGenre Context triple: [Golden Globe for I Never Promised You a Rose Garden, awardForGenre, dramatic cinema]
-
A.
awardGenreFocus
chosen
Indicates that an award specifically recognizes or emphasizes works within a particular genre.
-
B.
awardGivenBy
Indicates that an award is conferred or presented by one entity to another.
-
C.
genreOfAwards
Indicates the type or category of awards associated with a given work, event, or entity.
-
D.
awardType
Indicates the specific category or kind of award associated with an entity or event.
-
E.
awardLanguage
Indicates that an award is given specifically for works or achievements in a particular language.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded76445988190984b57de66e00c4a |
completed | April 15, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:56 a.m.