Triple
T12641057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkeley Springs, West Virginia |
E301896
|
entity |
| Predicate | waterFromSpringsUsedFor |
P68556
|
FINISHED |
| Object | bathing |
—
|
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: bathing | Statement: [Berkeley Springs, West Virginia, waterFromSpringsUsedFor, bathing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterFromSpringsUsedFor Context triple: [Berkeley Springs, West Virginia, waterFromSpringsUsedFor, bathing]
-
A.
waterUse
Indicates the amount or manner in which water is consumed, utilized, or withdrawn by an entity or activity.
-
B.
hasWaterUse
chosen
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
-
C.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
-
D.
waterSource
Indicates that one entity serves as the source or provider of water for another entity.
-
E.
waterSourceType
Indicates the kind or category of source from which water is obtained.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:17 p.m.