Triple
T23153070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Days of Mercy |
E578369
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Radek Ładczuk |
—
|
NE NERFINISHED |
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: Radek Ładczuk | Statement: [My Days of Mercy, cinematographyBy, Radek Ładczuk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radek Ładczuk Context triple: [My Days of Mercy, cinematographyBy, Radek Ładczuk]
-
A.
Radek Ladczuk
chosen
Radek Ladczuk is a Polish cinematographer best known for his atmospheric work on the acclaimed horror film "The Babadook."
-
B.
Rafał Katzer
Rafał Katzer is a Polish official who has served as the voivode (governor) of the Pomeranian Voivodeship.
-
C.
Karol Klimczak
Karol Klimczak is a Polish football executive best known for leading top-flight club Lech Poznań.
-
D.
Rafał Dutkiewicz
Rafał Dutkiewicz is a Polish politician and mathematician best known for serving as the long-time mayor of Wrocław, where he oversaw significant urban development and modernization.
-
E.
Radosław Dobrowolski
Radosław Dobrowolski is a Polish academic and administrator who serves as the rector of Maria Curie-Skłodowska University in Lublin.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18efaa1fc81908fb1987dbf732f46 |
completed | April 29, 2026, 4:54 a.m. |
Created at: April 17, 2026, 4:01 p.m.