Triple
T106198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luftbrücke |
E2141
|
entity |
| Predicate | numberOfFlights |
P4899
|
FINISHED |
| Object | over 200000 |
—
|
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: over 200000 | Statement: [Luftbrücke, numberOfFlights, over 200000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFlights Context triple: [Luftbrücke, numberOfFlights, over 200000]
-
A.
hasDomesticFlights
Indicates that an airline or airport operates flights within the same country, connecting domestic destinations.
-
B.
flightDuration
Indicates the length of time that a specific flight takes from departure to arrival.
-
C.
hasInternationalFlights
Indicates that an airport or airline operates flights connecting to destinations in other countries.
-
D.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
-
E.
numberOfRunways
Indicates the quantity of runways associated with a given entity, such as an airport or airfield.
- F. None of above. chosen
Provenance (4 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a256ec650c8190bee2067e37065527 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563d33788190999d471b486d5603 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256ea776081908fec36c3fdfb8d84 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.