Triple
T30877741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Higashiyama Mountains |
E786522
|
entity |
| Predicate | hasTraditionalDistrictNearby |
P75597
|
FINISHED |
| Object | Higashiyama District |
—
|
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 District | Statement: [Higashiyama Mountains, hasTraditionalDistrictNearby, Higashiyama District]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalDistrictNearby Context triple: [Higashiyama Mountains, hasTraditionalDistrictNearby, Higashiyama District]
-
A.
hasNearbyTraditionalVillage
chosen
Indicates that an entity is located close to or in the vicinity of a traditional village.
-
B.
hasTraditionalCountryNear
Indicates that one entity has a traditional or culturally recognized country located geographically close to it.
-
C.
hasLocalDistrict
Indicates that an entity is associated with or falls under the jurisdiction of a specific local administrative district.
-
D.
traditionalDistrict
Indicates that an entity is located in, associated with, or belongs to a historically recognized or customary administrative or cultural district.
-
E.
hasRelatedDistrict
Indicates that one entity is associated with, linked to, or falls within the scope of a particular district.
- 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_69f224bae17c8190bb3a6a28e3d019df |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fea1f5d8c481908dc3351dc9ecef7f |
completed | May 9, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69fea06b6fe0819095bf4c1bc9809927 |
completed | May 9, 2026, 2:48 a.m. |
Created at: April 29, 2026, 8:48 p.m.