Triple
T8298090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cedar Springs, Michigan |
E194271
|
entity |
| Predicate | waterSourceHistorically |
P12617
|
FINISHED |
| Object | natural springs |
—
|
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: natural springs | Statement: [Cedar Springs, Michigan, waterSourceHistorically, natural springs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterSourceHistorically Context triple: [Cedar Springs, Michigan, waterSourceHistorically, natural springs]
-
A.
waterSource
Indicates that one entity serves as the source or provider of water for another entity.
-
B.
waterSourceDedicatedTo
Indicates that a particular water source is specifically allocated or reserved for a designated use, group, or purpose.
-
C.
waterOrigin
chosen
Indicates the source or starting location from which the water originates or is supplied.
-
D.
waterSourceAfter
Indicates that one water source occurs, appears, or is accessed after another in time or sequence.
-
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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7dfa040c8190ab801b3910e39142 |
completed | March 31, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:53 p.m.