Triple
T28498852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Metropolitan Routes |
E721178
|
entity |
| Predicate | includesUrbanSections |
P147867
|
FINISHED |
| Object | central Tokyo |
—
|
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: central Tokyo | Statement: [Tokyo Metropolitan Routes, includesUrbanSections, central Tokyo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesUrbanSections Context triple: [Tokyo Metropolitan Routes, includesUrbanSections, central Tokyo]
-
A.
hasUrbanSectionsIn
chosen
Indicates that an entity includes or contains sections that are classified as urban within a specified area or region.
-
B.
isUrbanSectionOf
Indicates that one area or segment is the part of a larger entity that lies within an urban or city environment.
-
C.
hasUrbanFabric
Indicates that one entity possesses, contains, or is characterized by a particular pattern or structure of built-up urban development.
-
D.
hasUrbanConcept
Indicates that an entity is associated with, characterized by, or incorporates an urban-related concept, idea, or design principle.
-
E.
includesUrbanApproach
Indicates that something incorporates or accounts for an urban-focused method, perspective, or component within its overall approach.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69ff0491409c8190be40f633a58da0b1 |
completed | May 9, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69ff040bb5cc81909534c7eee85d5e90 |
completed | May 9, 2026, 9:53 a.m. |
Created at: April 28, 2026, 3:05 a.m.