Triple
T37616086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanagawa-juku |
E935923
|
entity |
| Predicate | travelNetworkRole |
P137851
|
FINISHED |
| Object | key node on the Tōkaidō |
—
|
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 node on the Tōkaidō | Statement: [Kanagawa-juku, travelNetworkRole, key node on the Tōkaidō]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelNetworkRole Context triple: [Kanagawa-juku, travelNetworkRole, key node on the Tōkaidō]
-
A.
travelRouteRole
chosen
Indicates the specific functional role an entity plays within a travel route, such as origin, destination, or intermediate stop.
-
B.
travelRole
Indicates the specific role or capacity an entity has in relation to a travel activity or journey (e.g., traveler, guide, driver).
-
C.
travelMechanic
Indicates the method or system by which movement or travel between locations is carried out.
-
D.
connectsTravelBetween
Indicates a relationship where something (such as a route, service, or mode of transport) enables or provides travel between two locations.
-
E.
tourRole
Indicates the specific function, capacity, or responsibility an entity has within the context of a tour.
- 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_69f76ed16b748190ad6add183b1be688 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: May 3, 2026, 4:18 p.m.