Triple
T4392961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bern Airport |
E99408
|
entity |
| Predicate | flightScope |
P56356
|
FINISHED |
| Object | short-haul |
—
|
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: short-haul | Statement: [Bern Airport, flightScope, short-haul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flightScope Context triple: [Bern Airport, flightScope, short-haul]
-
A.
shoots
Indicates that one entity propels a projectile or discharge toward another entity, typically with the intent to hit or affect it.
-
B.
shotDownOver
Indicates that one entity caused another (typically an aircraft or projectile) to be brought down while it was in flight above a particular location or area.
-
C.
shootingStyle
Indicates the characteristic manner or technique with which an entity performs a shooting action (e.g., in sports or photography).
-
D.
shootsCatches
Indicates that one entity shoots something that is then caught by another entity.
-
E.
hasShootingLocation
Indicates that an audiovisual work was filmed or recorded at a particular location.
- 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_69b345506b408190b0e3dee616738a7d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352a8862481909dc67abf42be6928 |
completed | March 12, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3501834448190bedf775a80da4778 |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:19 p.m.