Triple
T26190024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bodrum-Milas Airport |
E654936
|
entity |
| Predicate | hasSeasonalTraffic |
P29452
|
FINISHED |
| Object | high summer tourist traffic |
—
|
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: high summer tourist traffic | Statement: [Bodrum-Milas Airport, hasSeasonalTraffic, high summer tourist traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalTraffic Context triple: [Bodrum-Milas Airport, hasSeasonalTraffic, high summer tourist traffic]
-
A.
servesSeasonalTraffic
Indicates that an entity provides service only during specific seasons or periods of the year, rather than year-round.
-
B.
hasTrafficPattern
chosen
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
-
C.
hasSeasonalPattern
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
D.
hasSeasonalMigration
Indicates that an entity regularly moves between different locations according to seasonal or cyclical environmental changes.
-
E.
hasHeavyTraffic
Indicates that a location, route, or area is experiencing a high volume of traffic, causing congestion or delays.
- 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_69ee5b469bc081908fe486453fdad810 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
Created at: April 26, 2026, 8:44 p.m.