Triple
T29922816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 天草飛行場 |
E759991
|
entity |
| Predicate | 気象条件の特徴 |
P132755
|
FINISHED |
| Object | 海に囲まれた島嶼部特有の気象の影響を受ける |
—
|
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: 海に囲まれた島嶼部特有の気象の影響を受ける | Statement: [天草飛行場, 気象条件の特徴, 海に囲まれた島嶼部特有の気象の影響を受ける]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 気象条件の特徴 Context triple: [天草飛行場, 気象条件の特徴, 海に囲まれた島嶼部特有の気象の影響を受ける]
-
A.
typicalWeatherFeature
chosen
Indicates a weather condition or pattern that commonly characterizes a place or time period.
-
B.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
C.
防災上の特徴
Indicates a relationship where an entity possesses characteristics or features relevant to disaster prevention or mitigation.
-
D.
skyConditionAdvantage
Indicates that certain sky or weather conditions provide a beneficial effect or favorable advantage to an entity or activity.
-
E.
meteorologicalStatus
Indicates the current or historical weather-related condition or state affecting an entity or location.
- 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_69f2246189fc8190996b63ee1f9a2374 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f677953ad0819099fa0d8006a65679 |
completed | May 2, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:15 p.m.