Triple
T24719340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 川越市 |
E612252
|
entity |
| Predicate | 観光都市指定・評価 |
P62013
|
FINISHED |
| Object | 小江戸観光地として知られる |
—
|
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: 小江戸観光地として知られる | Statement: [川越市, 観光都市指定・評価, 小江戸観光地として知られる]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 観光都市指定・評価 Context triple: [川越市, 観光都市指定・評価, 小江戸観光地として知られる]
-
A.
hasTouristRank
Indicates that an entity is assigned a specific rank or rating based on its attractiveness or importance as a tourist destination.
-
B.
hasTourismRating
Indicates that an entity has been assigned a specific tourism-related quality or rating, reflecting its appeal or suitability for tourists.
-
C.
touristAttractionRanking
Indicates the relative position or level of appeal assigned to a tourist attraction compared to others, typically based on popularity, quality, or significance.
-
D.
areMajorTouristDestinations
Indicates that the referenced places are widely recognized and frequently visited as primary tourist destinations.
-
E.
touristDesignation
chosen
Indicates that a place or entity has been formally identified or labeled as a tourist attraction or destination.
- 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_69e2d7d6e7a48190bb43b0d8bb1137a0 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f410fe3b848190ae296a29f742ee30 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ee8ada8819089a7016b50308ff0 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 3:40 a.m.