Triple
T19779221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Näsinneula Observation Tower |
E475086
|
entity |
| Predicate | hasRestaurantHeight |
P58689
|
FINISHED |
| Object | approximately 124 metres |
—
|
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: approximately 124 metres | Statement: [Näsinneula Observation Tower, hasRestaurantHeight, approximately 124 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRestaurantHeight Context triple: [Näsinneula Observation Tower, hasRestaurantHeight, approximately 124 metres]
-
A.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
B.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
C.
hasRestaurantArea
Indicates that a place or establishment includes a designated area used as a restaurant or for dining services.
-
D.
hasRestaurantFloors
Indicates that a restaurant occupies or is distributed across a specified number of floors in a building.
-
E.
revolvingRestaurantHeight
chosen
Indicates the height at which a revolving restaurant is situated, typically measured from ground level or sea level.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6538230488190b45cd8aaec658f7f |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:49 p.m.