Triple
T10902895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Clair Township |
E257489
|
entity |
| Predicate | hasRiverfrontParks |
P50459
|
FINISHED |
| Object | St. Clair River shoreline parks |
—
|
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: St. Clair River shoreline parks | Statement: [St. Clair Township, hasRiverfrontParks, St. Clair River shoreline parks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverfrontParks Context triple: [St. Clair Township, hasRiverfrontParks, St. Clair River shoreline parks]
-
A.
hasRiverfrontDistrict
Indicates that a place includes a designated district or area that directly borders and is oriented around a river.
-
B.
hasWaterfrontPark
chosen
Indicates that a place or area includes or is associated with a park located directly along a body of water.
-
C.
hasRiverValleyPark
Indicates that a place includes or is associated with a park located in or along a river valley.
-
D.
hasParks
Indicates that one entity possesses, contains, or is associated with one or more parks.
-
E.
isRiverside
Indicates that one entity is located beside or along the bank of a river in relation to 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d761a4e9d48190b107839761a2152b |
completed | April 9, 2026, 8:21 a.m. |
| PD | Predicate disambiguation | batch_69d70d3d69e08190bb369e9a7927142c |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:22 p.m.