Triple
T29255126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E259 series EMU |
E741683
|
entity |
| Predicate | operatorServiceArea |
P82
|
FINISHED |
| Object | Tokyo metropolitan area |
—
|
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: Tokyo metropolitan area | Statement: [E259 series EMU, operatorServiceArea, Tokyo metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorServiceArea Context triple: [E259 series EMU, operatorServiceArea, Tokyo metropolitan area]
-
A.
areaOfService
Indicates the geographic or functional region within which a service is provided or applicable.
-
B.
serviceAreaName
Indicates the designated name of the geographic or functional area that a service covers or operates within.
-
C.
areaServed
chosen
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
D.
hasServiceAreas
Indicates that an entity provides services within, or is operational across, specific geographic or functional areas.
-
E.
nearbyAreaServed
Indicates that a location or entity provides services or coverage to an adjacent or nearby area.
- 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_69f0911eba2c8190b07cd2fdf91422c9 |
completed | April 28, 2026, 10:51 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, 12:36 p.m.