Triple
T727928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vallorbe–Jougne crossing |
E14767
|
entity |
| Predicate | roadImportance |
P19386
|
FINISHED |
| Object | major regional 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: major regional route | Statement: [Vallorbe–Jougne crossing, roadImportance, major regional route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadImportance Context triple: [Vallorbe–Jougne crossing, roadImportance, major regional route]
-
A.
roadType
Indicates the classification or category of a road based on its functional or physical characteristics.
-
B.
roadFeature
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
-
C.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
D.
roadJunctionIncludes
Indicates that a road junction spatially contains or encompasses a specific road segment or related roadway element as part of its structure.
-
E.
roadName
Indicates the specific name assigned to a road that identifies it within a transportation or address system.
- F. None of above. chosen
Provenance (4 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64adf2c81908e48090be35dd9d9 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f839608190878a60eb7a044ed9 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a64957ec81909fe2e2dbffd80ed3 |
completed | March 1, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:37 p.m.