Triple
T23938109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VisitOSLO area |
E602697
|
entity |
| Predicate | includesAttractionsType |
P8648
|
FINISHED |
| Object | museums |
—
|
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: museums | Statement: [VisitOSLO area, includesAttractionsType, museums]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesAttractionsType Context triple: [VisitOSLO area, includesAttractionsType, museums]
-
A.
containsAttraction
Indicates that one entity includes or encompasses an attraction (such as a point of interest, feature, or draw) within its bounds or scope.
-
B.
hasAttractionType
chosen
Indicates that one entity is associated with a specific kind or category of attraction (e.g., tourist, cultural, natural).
-
C.
partOfAttractionType
Indicates that one attraction type is a component or subset of a broader, more general attraction type.
-
D.
sponsoredAttractionType
Indicates that an attraction is sponsored in association with a particular type or category of attraction.
-
E.
attractionType
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
- 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_69e2953cf6e081909b8e25a10a52dddc |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1cfa267b88190a1e7d599f22441e2 |
completed | April 29, 2026, 9:30 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:07 p.m.