Triple
T9814276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Incahuasi Island |
E238358
|
entity |
| Predicate | transportHubForTours |
P17407
|
FINISHED |
| Object | stop on multi-day Salar de Uyuni tours |
—
|
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: stop on multi-day Salar de Uyuni tours | Statement: [Incahuasi Island, transportHubForTours, stop on multi-day Salar de Uyuni tours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportHubForTours Context triple: [Incahuasi Island, transportHubForTours, stop on multi-day Salar de Uyuni tours]
-
A.
transportHubType
Indicates the specific category or kind of transport hub associated with an entity (e.g., airport, train station, bus terminal).
-
B.
transportHubScope
Indicates the extent or range of areas, routes, or services that a particular transport hub covers or connects.
-
C.
touristGatewayTo
chosen
Indicates a relationship where one place serves as the primary access point or entry hub for tourists visiting another place.
-
D.
tourWith
Indicates that one entity accompanies another on a tour, sharing the same itinerary or guided experience.
-
E.
travelRouteOf
Indicates the path or itinerary that an entity follows or uses when traveling from one location to another.
- 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_69ca84defac48190abc1148804f184c1 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f19660819083e3f15780352052 |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:30 p.m.