Triple
T20701961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Autopsy of Jane Doe |
E508805
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Roman Osin |
—
|
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: Roman Osin | Statement: [The Autopsy of Jane Doe, cinematographyBy, Roman Osin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roman Osin Context triple: [The Autopsy of Jane Doe, cinematographyBy, Roman Osin]
-
A.
Roman Osin
chosen
Roman Osin is a cinematographer best known for his visually rich work on films such as the 2005 adaptation of "Pride and Prejudice."
-
B.
Oleg Krasnov
Oleg Krasnov is a person notable enough to be recognized as a significant bearer of the Krasnov surname.
-
C.
Roman Kondratenko
Roman Kondratenko was a Russian general renowned for his key role in organizing and leading the defense of Port Arthur during the Russo-Japanese War.
-
D.
Michael Antonov
Michael Antonov is a software engineer and entrepreneur best known as a co-founder and early architect of the virtual reality company Oculus VR.
-
E.
Oleg Losik
Oleg Losik was a Soviet military commander known for his leadership role during the Sino–Soviet border conflict of 1969.
- 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c18cb9cc819095d0669dca037424 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 12:12 p.m.