Triple
T10475906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camino de Santiago |
E247043
|
entity |
| Predicate | hasTypicalModeOfTravel |
P70707
|
FINISHED |
| Object | walking |
—
|
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: walking | Statement: [Camino de Santiago, hasTypicalModeOfTravel, walking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalModeOfTravel Context triple: [Camino de Santiago, hasTypicalModeOfTravel, walking]
-
A.
hasPrimaryTransportationMode
chosen
Indicates the main or most frequently used mode of transportation associated with an entity.
-
B.
hasPublicTransportUsage
Indicates that an entity makes use of, or is associated with the use of, public transportation services.
-
C.
hasSecondaryTransportationMode
Indicates that an entity is associated with an additional, non-primary mode of transportation it can use or provide.
-
D.
passesUsedForTransportation
Indicates that the passes are utilized as a means or instrument for transporting people or goods.
-
E.
hasPublicTransitMode
Indicates that a location, route, or service is associated with or supports a specific mode of public transportation (e.g., bus, train, tram).
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5094f6b408190a5a26b1a82e4a02b |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:21 p.m.