Triple
T32739098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clementine Kruczynski |
E837170
|
entity |
| Predicate | hasFavoriteDrink |
P8713
|
FINISHED |
| Object | alcoholic beverages (frequent drinking) |
—
|
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: alcoholic beverages (frequent drinking) | Statement: [Clementine Kruczynski, hasFavoriteDrink, alcoholic beverages (frequent drinking)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFavoriteDrink Context triple: [Clementine Kruczynski, hasFavoriteDrink, alcoholic beverages (frequent drinking)]
-
A.
favoriteDrink
chosen
Indicates that one entity has a preferred beverage over others.
-
B.
hasDrinkNamedAfter
Indicates that one entity has a beverage that is named after another entity.
-
C.
hasBeverageCategory
Indicates that an entity is associated with or classified under a particular beverage category.
-
D.
hasBeverageProduct
Indicates that one entity possesses, offers, or is associated with a particular beverage product.
-
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_69f34936e1748190b797e406e4e9293a |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd474b7e788190a9bb9b542d878f60 |
completed | May 8, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69fd46d8b2f0819099d92d72c902f60e |
completed | May 8, 2026, 2:13 a.m. |
Created at: May 1, 2026, 1:12 a.m.