Triple
T22210808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lena Olin |
E548937
|
entity |
| Predicate | notableRole |
P22
|
FINISHED |
| Object | Masha in Enemies, A Love Story |
—
|
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: Masha in Enemies, A Love Story | Statement: [Lena Olin, notableRole, Masha in Enemies, A Love Story]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masha in Enemies, A Love Story Context triple: [Lena Olin, notableRole, Masha in Enemies, A Love Story]
-
A.
Masha
chosen
Masha is a diminutive and affectionate Russian form of the given name Mary (Maria).
-
B.
Masha
Masha is a town in southwestern Ethiopia that serves as an administrative and commercial center in the Sheka Zone.
-
C.
Mashenka
Mashenka is a Russian diminutive form of the female given name Maria, often used affectionately for girls and women.
-
D.
My Friend Ivan Lapshin
My Friend Ivan Lapshin is a 1984 Soviet drama film by director Aleksei German, acclaimed for its atmospheric black-and-white portrayal of life in a provincial town in the pre–World War II Stalinist era.
-
E.
Love, Antosha
Love, Antosha is a 2019 documentary film that chronicles the life and career of actor Anton Yelchin through home videos, interviews, and personal writings.
- 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_69e11e3f7e04819089806d81d5ac431e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b2bcf748190a9721f0c9ae17e70 |
completed | April 28, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:36 p.m.