Triple
T8714854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rathaus-Glockenspiel |
E206867
|
entity |
| Predicate | touristSeasonality |
P53625
|
FINISHED |
| Object | heavily visited in summer months |
—
|
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: heavily visited in summer months | Statement: [Rathaus-Glockenspiel, touristSeasonality, heavily visited in summer months]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristSeasonality Context triple: [Rathaus-Glockenspiel, touristSeasonality, heavily visited in summer months]
-
A.
seasonalTourism
chosen
Indicates that tourism activity in a place varies significantly by season, with distinct peak and off-peak periods.
-
B.
touristArrivalsShareInTerritory
Indicates the proportion of total tourist arrivals that occur within a specific territory relative to a larger reference area or total.
-
C.
hasSeasonalPattern
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
D.
typicalVisitorsPerSeason
Indicates the usual number of visitors associated with each season for a given entity or location.
-
E.
typicalSeasonTiming
Indicates the usual time period or season during which something normally occurs or is expected to take place.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd6707c819092c9fca34f273d5e |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.