Triple
T37061595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 琵琶湖 |
E917336
|
entity |
| Predicate | 水質問題 |
P25191
|
FINISHED |
| Object | 富栄養化の進行 |
—
|
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: 富栄養化の進行 | Statement: [琵琶湖, 水質問題, 富栄養化の進行]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 水質問題 Context triple: [琵琶湖, 水質問題, 富栄養化の進行]
-
A.
waterQualityIssues
chosen
Indicates that there are problems or concerns with the condition, safety, or suitability of a water source.
-
B.
waterAppearance
Indicates how the water involved in the situation looks or visually appears (e.g., its color, clarity, or surface condition).
-
C.
waterCondition
Indicates the state or quality of water affecting an entity, such as its cleanliness, safety, or suitability for a particular use.
-
D.
waterQualityProtection
Indicates efforts, measures, or responsibilities aimed at preserving or improving the cleanliness, safety, and ecological integrity of water resources.
-
E.
hydrologicalIssue
Indicates a relationship where one entity is the subject or source of a problem, concern, or challenge related to water movement, distribution, or quality in the hydrological system.
- 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_69f76e95fa40819091e14681087ae5e4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.