Triple
T26013289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River of Five Colors |
E646957
|
entity |
| Predicate | colorEffectCause |
P23298
|
FINISHED |
| Object | aquatic plants attached to riverbed |
—
|
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: aquatic plants attached to riverbed | Statement: [River of Five Colors, colorEffectCause, aquatic plants attached to riverbed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorEffectCause Context triple: [River of Five Colors, colorEffectCause, aquatic plants attached to riverbed]
-
A.
colorInfluence
Indicates how the presence or use of one color affects the perception, appearance, or impact of another.
-
B.
colorationCause
chosen
Indicates that one entity is the cause or source of the coloration observed in another entity.
-
C.
colorTreatment
Indicates that an entity has undergone a process or action that changes, enhances, or assigns its color.
-
D.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
E.
colorUse
Indicates that one entity uses, applies, or is associated with a particular color in its appearance, design, or representation.
- 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_69e77e8aa65881909ca58918f29ab2a0 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f605b710ec8190a84765aee7ba31e1 |
completed | May 2, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 22, 2026, 9:02 a.m.