Triple
T558358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Synthetism |
E11992
|
entity |
| Predicate | lineTreatment |
P15027
|
FINISHED |
| Object | dark contour lines separating color zones |
—
|
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: dark contour lines separating color zones | Statement: [Synthetism, lineTreatment, dark contour lines separating color zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineTreatment Context triple: [Synthetism, lineTreatment, dark contour lines separating color zones]
-
A.
lineType
chosen
Indicates the specific category or style of a line used in a representation, such as its function or visual convention.
-
B.
lineUses
Indicates that a particular line (such as a route, service, or connection) makes use of or is implemented using a specified resource, infrastructure, or element.
-
C.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
-
D.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
E.
isLinedWith
Indicates that one object or surface is covered, edged, or internally coated along its length or area with another material or layer.
- 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_69a499df43f08190b514a38d36fc271d |
completed | March 1, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.