Triple
T6592948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Essa |
E148404
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Springwater |
E187525
|
NE 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: Springwater | Statement: [Essa, hasNeighboringMunicipality, Springwater]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Springwater Context triple: [Essa, hasNeighboringMunicipality, Springwater]
-
A.
Springwater
chosen
Springwater is a rural township in central Ontario, Canada, known for its agricultural landscape and proximity to the city of Barrie.
-
B.
West Water
West Water is a tributary stream of the North Esk River in eastern Scotland.
-
C.
Winter Brook
Winter Brook is a small stream that forms part of the Mystic River watershed in eastern Massachusetts.
-
D.
Stone Spring
Stone Spring is a science fiction novel by Stephen Baxter that reimagines prehistoric Britain facing a catastrophic sea-level rise and the resulting struggle for survival and adaptation.
-
E.
Sylvan Water
Sylvan Water is a picturesque pond within Brooklyn’s historic Green-Wood Cemetery, known for its tranquil scenery and surrounding monuments.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c687e7b8688190811ffee72e096468 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aecf50ac81909cb9960c8265a7ea |
completed | March 27, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d57d338c81909e935926d635d2fc |
completed | March 27, 2026, 7:07 p.m. |
Created at: March 27, 2026, 1:55 p.m.