Triple
T14904684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katakolo |
E360097
|
entity |
| Predicate | touristRole |
P71088
|
FINISHED |
| Object | cruise stop for Olympia excursions |
—
|
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: cruise stop for Olympia excursions | Statement: [Katakolo, touristRole, cruise stop for Olympia excursions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristRole Context triple: [Katakolo, touristRole, cruise stop for Olympia excursions]
-
A.
travelRole
Indicates the specific role or capacity an entity has in relation to a travel activity or journey (e.g., traveler, guide, driver).
-
B.
touristCharacter
chosen
Indicates that an entity has the role, behavior, or qualities characteristic of a tourist in relation to another entity or context.
-
C.
touristAccess
Indicates that a place or resource is available for use or visitation by tourists.
-
D.
roleInAttraction
Indicates the specific function or position an entity holds within the context of a particular attraction or point of interest.
-
E.
touristGatewayTo
Indicates a relationship where one place serves as the primary access point or entry hub for tourists visiting another place.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded60cd5588190b1efecc2b220da69 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:12 a.m.