Triple
T31498144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-Cinetone |
E803603
|
entity |
| Predicate | lookCharacteristic |
P311
|
FINISHED |
| Object | soft cinematic contrast |
—
|
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: soft cinematic contrast | Statement: [S-Cinetone, lookCharacteristic, soft cinematic contrast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lookCharacteristic Context triple: [S-Cinetone, lookCharacteristic, soft cinematic contrast]
-
A.
eyeCharacteristic
Indicates a relationship where an entity possesses a specific attribute, feature, or quality of its eyes.
-
B.
eyeFeatureObserved
Indicates that a specific characteristic or condition of the eye has been detected or recorded through observation.
-
C.
appearance
chosen
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
D.
spanCharacteristic
Indicates that one entity has a particular measurable or descriptive property that characterizes the extent, duration, or range of another entity or phenomenon.
-
E.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
- 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_69f348cae52081909fa8e5f697523ae3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a1eac8688190afdf5732cedf086d |
completed | May 3, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69f69fe82e5c81909da9db0a2f3bba6d |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:42 p.m.