Triple
T1005865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CinemaScope |
E21708
|
entity |
| Predicate | notableFilm |
P22
|
FINISHED |
| Object | Anastasia |
E110789
|
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: Anastasia | Statement: [CinemaScope, notableFilm, Anastasia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anastasia Context triple: [CinemaScope, notableFilm, Anastasia]
-
A.
Anastasia
chosen
Anastasia is a 1956 historical drama film starring Ingrid Bergman as an amnesiac woman who may be the surviving daughter of Russia’s last tsar.
-
B.
Anastasia Shubskaya
Anastasia Shubskaya is a Russian model and film producer best known as the wife of NHL star Alex Ovechkin.
-
C.
Anastasia Virganskaya
Anastasia Virganskaya is the granddaughter of former Soviet leader Mikhail Gorbachev and the daughter of his only child, Irina Virganskaya.
-
D.
Diana
Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
-
E.
Tatyana
Tatyana is a feminine given name of Slavic origin, particularly common in Russian-speaking countries.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b51303548190a5ee3c0797fc3245 |
completed | March 1, 2026, 9:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac428db9bc81909304802e2b50686c |
completed | March 7, 2026, 3:21 p.m. |
Created at: March 1, 2026, 7:41 p.m.