Triple
T4889456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Motomachi |
E109520
|
entity |
| Predicate | roleInTourism |
P33155
|
FINISHED |
| Object | key sightseeing spot in Yokohama |
—
|
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: key sightseeing spot in Yokohama | Statement: [Motomachi, roleInTourism, key sightseeing spot in Yokohama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTourism Context triple: [Motomachi, roleInTourism, key sightseeing spot in Yokohama]
-
A.
hasTourismFunction
chosen
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
B.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
C.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
D.
roleInAttraction
Indicates the specific function or position an entity holds within the context of a particular attraction or point of interest.
-
E.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.