Triple

T31498115
Position Surface form Disambiguated ID Type / Status
Subject S-Cinetone E803603 entity
Predicate saturationCharacteristic P171704 FINISHED
Object moderate color saturation 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: moderate color saturation | Statement: [S-Cinetone, saturationCharacteristic, moderate color saturation]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: saturationCharacteristic
Context triple: [S-Cinetone, saturationCharacteristic, moderate color saturation]
  • A. spanCharacteristic
    Indicates that one entity has a particular measurable or descriptive property that characterizes the extent, duration, or range of another entity or phenomenon.
  • B. contrastCharacteristic
    Indicates that two entities are being compared by highlighting opposing or significantly different characteristics between them.
  • C. valueCharacteristic
    Indicates that one entity serves as a value or specific quantitative/qualitative measure that characterizes or describes another entity.
  • D. densityCharacteristic
    Indicates that one entity specifies or characterizes the density property or density-related attribute of another entity.
  • E. dataCharacteristic
    Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
  • F. None of above. chosen

Provenance (4 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.
PDg Predicate description generation batch_69f6a0e920cc8190a943fdd0594906c5 completed May 3, 2026, 1:12 a.m.
Created at: April 30, 2026, 9:42 p.m.