Triple
T3067848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantastic Four (2015 film) |
E62148
|
entity |
| Predicate | hasDarkerTone |
P44222
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Fantastic Four (2015 film), hasDarkerTone, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDarkerTone Context triple: [Fantastic Four (2015 film), hasDarkerTone, true]
-
A.
isDarkerThan
Indicates that one entity has a lower brightness or lightness level than another, making it visually darker in comparison.
-
B.
isShadeOf
Indicates that one entity represents a specific tonal or color variation derived from or closely related to another entity.
-
C.
hasMainContrast
Indicates a primary opposing or differing relationship between two elements, highlighting the main point of contrast between them.
-
D.
hasComplementaryColor
Indicates that one color is the complementary (i.e., opposite on the color wheel, providing maximum contrast) counterpart of another color.
-
E.
hasFleshColor
Indicates that an entity possesses a particular color or characteristic of its flesh or internal tissue.
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fea06881909e5251eea26599ac |
completed | March 8, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69ad9624b7a0819091d255614f5819ea |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f7630c81908e1ca8a69611cff6 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 3:02 p.m.