Triple
T37061551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 琵琶湖 |
E917336
|
entity |
| Predicate | 生態系の特徴 |
P22447
|
FINISHED |
| Object | 固有種が多い古代湖の生態系 |
—
|
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: 固有種が多い古代湖の生態系 | Statement: [琵琶湖, 生態系の特徴, 固有種が多い古代湖の生態系]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 生態系の特徴 Context triple: [琵琶湖, 生態系の特徴, 固有種が多い古代湖の生態系]
-
A.
partOfEcosystem
Indicates that an entity functions as a component within a larger ecological system, contributing to and affected by its interactions and processes.
-
B.
environmentalFeatureOf
Indicates a relationship where one entity is a natural or environmental characteristic, component, or attribute of another entity or place.
-
C.
ecosystemTerm
Indicates that one entity is a term, label, or concept used within the context of an ecosystem or ecological system.
-
D.
ecosystemRelevance
Indicates the degree to which something is important, impactful, or integral to the functioning or health of a particular ecosystem.
-
E.
hasBiodiversityFeature
chosen
Indicates that an entity possesses or is associated with a specific biodiversity-related characteristic, attribute, or element.
- 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.