Triple
T2757938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanikai Beach |
E61149
|
entity |
| Predicate | waterConditions |
P27141
|
FINISHED |
| Object | generally calm |
—
|
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: generally calm | Statement: [Lanikai Beach, waterConditions, generally calm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterConditions Context triple: [Lanikai Beach, waterConditions, generally calm]
-
A.
waterCondition
chosen
Indicates the state or quality of water affecting an entity, such as its cleanliness, safety, or suitability for a particular use.
-
B.
waterColor
Indicates that one entity is the color or hue characteristic of water associated with another entity.
-
C.
waterContains
Indicates that a body or volume of water holds, includes, or has within it a specified substance, object, or entity.
-
D.
hasWaterClarity
Indicates the degree to which water in a given context is clear, transparent, or free from visible impurities.
-
E.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb8ba4688190b401b6eb5b734ac6 |
completed | March 7, 2026, 8:02 a.m. |
| PD | Predicate disambiguation | batch_69abd82de7f48190acd614f28644c6da |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:57 p.m.