Triple
T28342048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niiza |
E717838
|
entity |
| Predicate | railCommuterFlow |
P94058
|
FINISHED |
| Object | to 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: to central Tokyo | Statement: [Niiza, railCommuterFlow, to central Tokyo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railCommuterFlow Context triple: [Niiza, railCommuterFlow, to central Tokyo]
-
A.
passengerFlowFeature
chosen
Indicates a characteristic or attribute that describes how passengers move or are distributed within a transport system or facility.
-
B.
commuterRailMode
Indicates that the relationship involves travel or transportation specifically by commuter rail as the mode of transit between the related entities.
-
C.
railwayTraffic
Indicates the presence, flow, or management of train movements along railway lines between locations.
-
D.
rapidTransitSystem
Indicates a transportation relationship where people or goods are moved via a high-capacity, high-frequency public transit system designed for rapid travel over urban or regional routes.
-
E.
coordinatesRailTrafficWith
Indicates that one entity organizes and synchronizes rail operations or movements with another entity to ensure coordinated train traffic.
- 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_69eff6eb30388190b898b96c4be6f49d |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64bd8d1848190835efdf5020b54cb |
completed | May 2, 2026, 7:09 p.m. |
| PD | Predicate disambiguation | batch_69f641e2f1708190b45b48d6a43c51d2 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 28, 2026, 12:40 a.m.