Triple
T34102096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usedomer Bäderbahn GmbH |
E874598
|
entity |
| Predicate | hasSeasonalDemandPattern |
P955
|
FINISHED |
| Object | higher traffic in summer season |
—
|
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: higher traffic in summer season | Statement: [Usedomer Bäderbahn GmbH, hasSeasonalDemandPattern, higher traffic in summer season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalDemandPattern Context triple: [Usedomer Bäderbahn GmbH, hasSeasonalDemandPattern, higher traffic in summer season]
-
A.
hasSeasonalPattern
chosen
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
B.
seasonalDemandPeak
Indicates that demand for a product, service, or resource reaches its highest level during a specific recurring season or time period.
-
C.
hasSeasonalStructure
Indicates that something exhibits a recurring pattern, organization, or behavior that varies systematically with the seasons.
-
D.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
E.
hasSeasonFrequency
Indicates how often something occurs or is scheduled within a specific season.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffa15d53208190ab8574d6c7913e18 |
completed | May 9, 2026, 9:04 p.m. |
| PD | Predicate disambiguation | batch_69ff9eee681c81909434e79c627cb528 |
completed | May 9, 2026, 8:54 p.m. |
Created at: May 1, 2026, 1:53 a.m.