Triple
T12272851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Lake, North Carolina |
E292512
|
entity |
| Predicate | lakeWaterClarity |
P15328
|
FINISHED |
| Object | high water clarity |
—
|
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: high water clarity | Statement: [White Lake, North Carolina, lakeWaterClarity, high water clarity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lakeWaterClarity Context triple: [White Lake, North Carolina, lakeWaterClarity, high water clarity]
-
A.
hasWaterClarity
chosen
Indicates the degree to which water in a given context is clear, transparent, or free from visible impurities.
-
B.
waterAppearance
Indicates how the water involved in the situation looks or visually appears (e.g., its color, clarity, or surface condition).
-
C.
waterColor
Indicates that one entity is the color or hue characteristic of water associated with another entity.
-
D.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
E.
surfaceWater
Indicates that one entity consists of or contains surface-level water associated with another entity.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.