Triple
T13304236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie Kroitor |
E316892
|
entity |
| Predicate | father |
P120
|
FINISHED |
| Object | Roman Kroitor |
E50143
|
NE 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: Roman Kroitor | Statement: [Julie Kroitor, father, Roman Kroitor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roman Kroitor Context triple: [Julie Kroitor, father, Roman Kroitor]
-
A.
Roman Kroitor
chosen
Roman Kroitor was a Canadian filmmaker and innovator best known as a co-founder and creative pioneer of the IMAX large-format cinema technology.
-
B.
Branko Lustig
Branko Lustig was a Croatian film producer and Holocaust survivor best known for his Academy Award–winning work on major historical epics such as Schindler’s List and Gladiator.
-
C.
Konrad V Kantner
Konrad V Kantner was a 14th-century Silesian duke from the Piast dynasty who ruled parts of the Głogów region.
-
D.
Ivan Rerberg
Ivan Rerberg was a prominent early 20th-century Russian architect and engineer known for his influential contributions to Moscow’s urban landscape and modernist architecture.
-
E.
Paul Varjak
Paul Varjak is a struggling writer and Holly Golightly’s neighbor and love interest in Truman Capote’s novella and the film adaptation "Breakfast at Tiffany’s."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990a76adc8190ab9abcdb79a21ca8 |
completed | April 11, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f262fd88190ba8871f8761a660b |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 9, 2026, 9:28 p.m.