Triple
T14250774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ikenoue Station |
E353253
|
entity |
| Predicate | hasNearbyResidentialArea |
P19783
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Ikenoue Station, hasNearbyResidentialArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyResidentialArea Context triple: [Ikenoue Station, hasNearbyResidentialArea, yes]
-
A.
hasResidentialArea
Indicates that an entity includes, contains, or is associated with an area designated for people to live or reside.
-
B.
hasNearbyLandUse
chosen
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
C.
residesNear
Indicates that one entity lives or is located in close physical proximity to another entity.
-
D.
hasNearbyDevelopment
Indicates that a development or construction project exists in close physical proximity to the referenced entity.
-
E.
isResidentialBaseFor
Indicates that a location serves as the primary place of residence or home base for a person or group.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6296f9d0819086f62f525d07eb12 |
completed | April 14, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69de05c09b7881908acbca18bd7d997c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.