Triple
T28948146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 稲城市 |
E730934
|
entity |
| Predicate | 観光・レジャー |
P33155
|
FINISHED |
| Object | よみうりランド最寄り自治体の一つ |
—
|
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: よみうりランド最寄り自治体の一つ | Statement: [稲城市, 観光・レジャー, よみうりランド最寄り自治体の一つ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 観光・レジャー Context triple: [稲城市, 観光・レジャー, よみうりランド最寄り自治体の一つ]
-
A.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
B.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
-
C.
tourismEvent
Indicates an event or activity that is organized for or significantly involves tourism, attracting visitors for leisure, cultural, or recreational purposes.
-
D.
hasTourismIndustry
Indicates that a place or region possesses an established tourism industry, involving organized services and activities catering to visitors and travelers.
-
E.
hasTourismFunction
chosen
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65b8a9a6c819091b9ec4563704490 |
completed | May 2, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:42 a.m.