Triple
T25096119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 熊本市 |
E628592
|
entity |
| Predicate | 観光キャッチフレーズ |
P25952
|
FINISHED |
| Object | 火の国・水の都 |
—
|
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: 火の国・水の都 | Statement: [熊本市, 観光キャッチフレーズ, 火の国・水の都]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 観光キャッチフレーズ Context triple: [熊本市, 観光キャッチフレーズ, 火の国・水の都]
-
A.
tourismSlogan
chosen
Indicates that a phrase is used as a promotional slogan to attract tourists to a place or destination.
-
B.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
-
C.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
D.
tourismCharacteristic
Indicates that something has a specific feature, quality, or attribute relevant to tourism, such as what makes a place, service, or activity notable or suitable for tourists.
-
E.
featuresCatchphrase
Indicates that an entity prominently includes or is associated with a particular catchphrase.
- 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_69e2ff2f58e881908340527bc5d34f07 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f464b9651481908d4d7584717f5c59 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:25 a.m.