Triple
T13410937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hauptmarkt (Nuremberg) |
E320082
|
entity |
| Predicate | ChristmasMarketFrequency |
P78772
|
FINISHED |
| Object | annual |
—
|
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: annual | Statement: [Hauptmarkt (Nuremberg), ChristmasMarketFrequency, annual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ChristmasMarketFrequency Context triple: [Hauptmarkt (Nuremberg), ChristmasMarketFrequency, annual]
-
A.
hasFestivalFrequency
chosen
Indicates how often a festival or recurring celebratory event takes place within a given time period.
-
B.
carnivalFrequency
Indicates how often a carnival event occurs within a given time period.
-
C.
typicalHolidaySeasonOutput
Indicates the usual or expected level of output or activity that occurs during the holiday season.
-
D.
winterFrequency
Indicates how often the related event, condition, or phenomenon occurs during the winter season.
-
E.
marketFrequency
Indicates how often a particular market-related event, activity, or transaction occurs within a given time period.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb3facc819088c1af3b59237e7a |
completed | April 12, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:35 p.m.