Triple
T25260939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Letters of a Russian Traveller |
E633300
|
entity |
| Predicate | travelRouteIncludes |
P79601
|
FINISHED |
| Object | Switzerland |
—
|
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: Switzerland | Statement: [Letters of a Russian Traveller, travelRouteIncludes, Switzerland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelRouteIncludes Context triple: [Letters of a Russian Traveller, travelRouteIncludes, Switzerland]
-
A.
travelRouteContext
Indicates the contextual details (such as purpose, conditions, or circumstances) under which a particular travel route is taken or defined.
-
B.
travelRouteOf
chosen
Indicates the path or itinerary that an entity follows or uses when traveling from one location to another.
-
C.
travelRouteRole
Indicates the specific functional role an entity plays within a travel route, such as origin, destination, or intermediate stop.
-
D.
transportIncludes
Indicates that a broader transport operation or service encompasses, contains, or makes use of a specific transport segment, mode, or component as part of its overall movement.
-
E.
tourWith
Indicates that one entity accompanies another on a tour, sharing the same itinerary or guided experience.
- 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_69e75a922ad481908f4f1f884583cb42 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f483935ecc8190979f4ad83b192919 |
completed | May 1, 2026, 10:42 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 21, 2026, 1:13 p.m.