Triple
T17840774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jindaiji Temple |
E445516
|
entity |
| Predicate | hasNearbyBusinessType |
P75188
|
FINISHED |
| Object | soba restaurants |
—
|
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: soba restaurants | Statement: [Jindaiji Temple, hasNearbyBusinessType, soba restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyBusinessType Context triple: [Jindaiji Temple, hasNearbyBusinessType, soba restaurants]
-
A.
hasNearbySiteType
Indicates that one entity has another entity of a specified site type located in its close physical vicinity.
-
B.
nearbyFacilityType
chosen
Indicates that a facility of a specified type is located close to a given reference entity or location.
-
C.
hasNearbyPropertyType
Indicates that one entity has another entity of a specified property type located in close physical proximity to it.
-
D.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
E.
hasNearbyIndustry
Indicates that an entity is located close to one or more industrial facilities or activities.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48d2b2ea08190926ec0cf01285833 |
completed | April 19, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e266888190ae976b4b7d5b886f |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:16 a.m.