Triple
T15653449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Route 139 |
E376368
|
entity |
| Predicate | hasRouteClassification |
P79318
|
FINISHED |
| Object | national route |
—
|
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: national route | Statement: [National Route 139, hasRouteClassification, national route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteClassification Context triple: [National Route 139, hasRouteClassification, national route]
-
A.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
B.
hasJISRouteClassification
chosen
Indicates that a route is assigned a specific classification according to the Japanese Industrial Standards (JIS) route categorization system.
-
C.
hasRouteFeature
Indicates that a route possesses or is associated with a specific characteristic, attribute, or feature.
-
D.
hasMajorRouteType
Indicates that an entity is associated with a primary classification of transportation route (such as highway, rail line, or other major route type).
-
E.
usesClassificationCriteria
Indicates that one entity applies specific classification criteria to categorize, organize, or evaluate another entity.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef089948190902ec22f4d7bc932 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.