Triple
T20295192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Dürkheim |
E505328
|
entity |
| Predicate | WurstmarktFrequency |
P139574
|
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: [Bad Dürkheim, WurstmarktFrequency, annual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WurstmarktFrequency Context triple: [Bad Dürkheim, WurstmarktFrequency, annual]
-
A.
famousMarket
Indicates that a market is widely known and recognized, typically for its popularity, historical significance, or distinctive offerings.
-
B.
cheeseMarketDay
Indicates a specific day designated for buying, selling, or trading cheese in a market setting.
-
C.
hasChristmasMarket
Indicates that a place or entity hosts or features a Christmas market.
-
D.
hasMarketHall
Indicates that an entity possesses, contains, or is associated with a market hall as part of its facilities or structures.
-
E.
sideOfBerlin
Indicates a spatial or political relationship specifying on which side or sector of Berlin an entity is located or associated.
- 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6770714c4819080e3256325747ebf |
completed | April 20, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56702ad04819099c1c08f28d16809 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 16, 2026, 11:15 a.m.