Triple
T1645474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin TV Tower |
E35571
|
entity |
| Predicate | elevatorSpeed |
P2096
|
FINISHED |
| Object | 6 m/s |
—
|
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: 6 m/s | Statement: [Berlin TV Tower, elevatorSpeed, 6 m/s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: elevatorSpeed Context triple: [Berlin TV Tower, elevatorSpeed, 6 m/s]
-
A.
numberOfElevators
Indicates the total count of elevators associated with a given entity or location.
-
B.
hasElevators
Indicates that one entity is equipped with or contains one or more elevators for vertical transportation.
-
C.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
-
D.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
-
E.
maxSpeed
chosen
Indicates the greatest possible speed at which an entity can move or operate under specified conditions.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a919306fd48190a245fc95e0e759d9 |
completed | March 5, 2026, 5:48 a.m. |
| PD | Predicate disambiguation | batch_69a907cc9d348190b76b0d3f596e5a81 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.