Triple
T36455026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 本栖湖 |
E898127
|
entity |
| Predicate | 透明度 |
P40821
|
FINISHED |
| Object | 高い |
—
|
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: 高い | Statement: [本栖湖, 透明度, 高い]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 透明度 Context triple: [本栖湖, 透明度, 高い]
-
A.
transparency
Indicates that an entity’s internal processes, information, or decision-making are openly accessible and understandable to others.
-
B.
isTransparentTo
chosen
Indicates that one entity allows another entity (such as light, information, or influence) to pass through or be perceived without obstruction or concealment.
-
C.
transparencyRole
Indicates that one entity serves a function or position related to ensuring or embodying transparency in relation to another entity.
-
D.
hasTransparencyRequirement
Indicates that one entity is obligated to provide clear, accessible information or disclosure to another entity or to the public.
-
E.
transparencyEffects
Indicates how the level or presence of transparency in one entity influences the perception, behavior, or properties of 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_69f76e57f08481908593bd0bc34581c8 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.