Triple
T19040581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg TV Tower |
E465988
|
entity |
| Predicate | restaurantHeight |
P58689
|
FINISHED |
| Object | approximately 132 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 132 metres | Statement: [Hamburg TV Tower, restaurantHeight, approximately 132 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restaurantHeight Context triple: [Hamburg TV Tower, restaurantHeight, approximately 132 metres]
-
A.
restaurantContained
Indicates that a restaurant is physically located within or is a part of a larger place or establishment.
-
B.
restaurantName
Indicates the name assigned to a restaurant as its identifying label.
-
C.
hasRestaurantFloors
Indicates that a restaurant occupies or is distributed across a specified number of floors in a building.
-
D.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d80054c88190a9d3a49aed504235 |
completed | April 20, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69e4a3001e388190aa6057266514e75a |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.