Triple
T21525769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JS17 |
E531091
|
entity |
| Predicate | stationNumberingSystem |
P44484
|
FINISHED |
| Object | JR East station numbering |
—
|
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: JR East station numbering | Statement: [JS17, stationNumberingSystem, JR East station numbering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stationNumberingSystem Context triple: [JS17, stationNumberingSystem, JR East station numbering]
-
A.
hasRailwayStationNumberingSystem
chosen
Indicates that a railway station is associated with a specific system for assigning it an identifying number or code.
-
B.
railwayLineNumberingSystem
Indicates a system that assigns and manages identifying numbers for railway lines within a rail network.
-
C.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
-
D.
hasStreetNumberingSystem
Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
-
E.
stationingBasis
Indicates the underlying reason, justification, or criteria for assigning or positioning an entity at a particular location or post.
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee885073888190ae49f967f72acbf8 |
completed | April 26, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:26 p.m.