Triple
T16764640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prague Christmas Market |
E407431
|
entity |
| Predicate | offersDrink |
P63281
|
FINISHED |
| Object | mulled wine |
—
|
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: mulled wine | Statement: [Prague Christmas Market, offersDrink, mulled wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersDrink Context triple: [Prague Christmas Market, offersDrink, mulled wine]
-
A.
offersMeal
Indicates that one entity provides or makes available a meal to another entity.
-
B.
offersObject
chosen
Indicates that a subject provides or makes available a specific object to another party as an offer.
-
C.
offersFoodAndBeverage
Indicates that an entity provides both food and drink to another entity or for general consumption.
-
D.
drinks
Indicates that one entity consumes a liquid substance, typically by ingesting it through the mouth.
-
E.
drinksWith
Indicates that two entities consume beverages together, typically at the same time and place in a social context.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abf126408190bd0365eca150f745 |
completed | April 18, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69e319cbd79c8190a03587a61c18bec0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:21 a.m.