Triple
T32638997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Way |
E834428
|
entity |
| Predicate | isMostPopularRouteOf |
P45128
|
FINISHED |
| Object | Camino de Santiago |
—
|
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: Camino de Santiago | Statement: [French Way, isMostPopularRouteOf, Camino de Santiago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMostPopularRouteOf Context triple: [French Way, isMostPopularRouteOf, Camino de Santiago]
-
A.
isMostPopularRouteOn
Indicates that a particular route is the most frequently chosen or favored option on a given transportation line, network, or service.
-
B.
isMostCommonRouteTo
chosen
Indicates that one route is the most frequently used or typical way to reach a particular destination or outcome compared to all other possible routes.
-
C.
popularityRelativeToOtherRoutes
Indicates how popular a given route is compared to other available routes.
-
D.
popularRouteTo
Indicates that one location is widely used or frequently chosen as a route or way to reach another location.
-
E.
popularRouteOn
Indicates that a particular route is frequently used or favored on a given transportation line, service, or network.
- 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c775d6188190b236fc4f89a11b61 |
completed | May 3, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:07 a.m.