Triple
T33582438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Motoyama Station |
E860183
|
entity |
| Predicate | nearbyCityFacility |
P61270
|
FINISHED |
| Object | Higashiyama Zoo and Botanical Gardens (via connecting transport) |
—
|
NE NERFINISHED |
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: Higashiyama Zoo and Botanical Gardens (via connecting transport) | Statement: [Motoyama Station, nearbyCityFacility, Higashiyama Zoo and Botanical Gardens (via connecting transport)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCityFacility Context triple: [Motoyama Station, nearbyCityFacility, Higashiyama Zoo and Botanical Gardens (via connecting transport)]
-
A.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
B.
nearbyFacilityCountry
Indicates that a facility is located in or near the specified country.
-
C.
infrastructureNearby
Indicates that one entity is located close to another entity that serves as infrastructure (such as roads, utilities, or public facilities).
-
D.
nearbyFacilityType
Indicates that a facility of a specified type is located close to a given reference entity or location.
-
E.
nearbyLocation
chosen
Indicates that one location is situated close to another location in physical space.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
Created at: May 1, 2026, 1:40 a.m.