Triple
T26158870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flatland River |
E660047
|
entity |
| Predicate | hasTextureCharacteristic |
P96596
|
FINISHED |
| Object | thick paint application |
—
|
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: thick paint application | Statement: [Flatland River, hasTextureCharacteristic, thick paint application]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextureCharacteristic Context triple: [Flatland River, hasTextureCharacteristic, thick paint application]
-
A.
usesTexture
Indicates that one entity employs or incorporates the texture of another entity in its appearance, design, or representation.
-
B.
textureCharacteristicInFugue
Indicates that a specified texture characteristic is present or manifested within a particular fugue.
-
C.
textureFeatures
chosen
Indicates that one entity possesses or is characterized by specific surface or material texture properties described by the other entity.
-
D.
hasHumanCharacteristic
Indicates that an entity possesses a trait, quality, or behavior typically associated with humans.
-
E.
hasBrightOrchestrationOrTexture
Indicates that the music exhibits a vivid, clear, or shimmering orchestral sound or instrumental texture.
- 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_69ee5bc5a9908190899d39ce95c6d215 |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 26, 2026, 8:29 p.m.