Triple
T10169621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Colorado River |
E235295
|
entity |
| Predicate | waterColorCharacteristic |
P13022
|
FINISHED |
| Object | often turquoise blue in lower canyon reaches |
—
|
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: often turquoise blue in lower canyon reaches | Statement: [Little Colorado River, waterColorCharacteristic, often turquoise blue in lower canyon reaches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterColorCharacteristic Context triple: [Little Colorado River, waterColorCharacteristic, often turquoise blue in lower canyon reaches]
-
A.
waterColor
Indicates that one entity is the color or hue characteristic of water associated with another entity.
-
B.
hasWaterColor
chosen
Indicates that an entity possesses or is characterized by a particular color of water.
-
C.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
D.
hasWaterBodyCharacteristic
Indicates that a water body possesses a specified physical, chemical, or ecological characteristic.
-
E.
waterAppearance
Indicates how the water involved in the situation looks or visually appears (e.g., its color, clarity, or surface condition).
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9ba56481908b5265aea8ea8cbe |
completed | April 2, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.