Triple
T551138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Cinematography |
E11841
|
entity |
| Predicate | colorCategoryIntroduced |
P3297
|
FINISHED |
| Object | 1939 |
—
|
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: 1939 | Statement: [Academy Award for Best Cinematography, colorCategoryIntroduced, 1939]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorCategoryIntroduced Context triple: [Academy Award for Best Cinematography, colorCategoryIntroduced, 1939]
-
A.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
introducedAsBrandBy
Indicates that one entity was presented or launched to the public or a market as a brand by another entity.
-
C.
introducedInYear
chosen
Indicates the year in which something was first introduced, launched, or made available.
-
D.
introducedDuring
Indicates that one entity was first brought into existence, use, or awareness within the time period, event, or context specified by the other entity.
-
E.
colorOftenUsed
Indicates that a particular color is frequently used or commonly applied in relation to something.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499030cf4819089b9163102255e49 |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.