Triple
T29128451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 長良川 |
E738298
|
entity |
| Predicate | waterQualityReputation |
P181142
|
FINISHED |
| Object | one of the clearest rivers in Japan |
—
|
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: one of the clearest rivers in Japan | Statement: [長良川, waterQualityReputation, one of the clearest rivers in Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterQualityReputation Context triple: [長良川, waterQualityReputation, one of the clearest rivers in Japan]
-
A.
wellWaterReputedFor
Indicates that a particular well’s water is widely regarded or reputed to have specific qualities, properties, or benefits.
-
B.
waterQualityIssues
Indicates that there are problems or concerns with the condition, safety, or suitability of a water source.
-
C.
waterQualityProtection
Indicates efforts, measures, or responsibilities aimed at preserving or improving the cleanliness, safety, and ecological integrity of water resources.
-
D.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
-
E.
hasWaterQualityHistory
Indicates that an entity is associated with a record or series of records describing changes or measurements of its water quality over time.
- 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_69f07cb29cdc8190afa55444553de60c |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
| PDg | Predicate description generation | batch_69f762651e088190baa21f25378a6065 |
completed | May 3, 2026, 2:57 p.m. |
Created at: April 28, 2026, 11:30 a.m.