Triple
T17800317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Mathias-sur-Richelieu |
E444404
|
entity |
| Predicate | hasRiverineCharacteristic |
P128972
|
FINISHED |
| Object | riverside municipality |
—
|
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: riverside municipality | Statement: [Saint-Mathias-sur-Richelieu, hasRiverineCharacteristic, riverside municipality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverineCharacteristic Context triple: [Saint-Mathias-sur-Richelieu, hasRiverineCharacteristic, riverside municipality]
-
A.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
B.
hasWatershedCharacteristic
Indicates that a watershed possesses a specified characteristic, feature, or property.
-
C.
hasWaterBodyCharacteristic
Indicates that a water body possesses a specified physical, chemical, or ecological characteristic.
-
D.
hasRiverInfluence
Indicates that one entity affects or is affected by a river in terms of its characteristics, behavior, or conditions.
-
E.
hasWatercourseType
Indicates the specific kind or category of watercourse (such as river, stream, or canal) associated with an entity.
- F. None of above. chosen
Provenance (4 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487ff42108190b82ceb4466aa2dff |
completed | April 19, 2026, 7:45 a.m. |
| PD | Predicate disambiguation | batch_69e3d8de28688190844b65acf6af54e6 |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:13 a.m.