Triple
T19098058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noce Blanche |
E467458
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Ludmila Mikaël |
—
|
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: Ludmila Mikaël | Statement: [Noce Blanche, starring, Ludmila Mikaël]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludmila Mikaël Context triple: [Noce Blanche, starring, Ludmila Mikaël]
-
A.
Ludmila Mikaël
chosen
Ludmila Mikaël is a French actress known for her work in film, theatre, and television since the late 1960s.
-
B.
Ludmilla
Ludmilla is a coastal suburb of Darwin in Australia's Northern Territory, known for its residential areas and proximity to Fannie Bay.
-
C.
Ludmila
Ludmila is the heroine of Alexander Pushkin’s narrative poem "Ruslan and Ludmila," known as a beautiful Kievan princess whose abduction sets the story’s adventurous plot in motion.
-
D.
Elena Milashina
Elena Milashina is a prominent Russian investigative journalist known for her reporting on human rights abuses, particularly in Chechnya, for the independent newspaper Novaya Gazeta.
-
E.
Liliana Mumy
Liliana Mumy is an American actress and voice actress known for her roles in family films and animated television series such as "Cheaper by the Dozen" and "The Loud House."
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36b279c819091a8d51f044bc644 |
completed | April 20, 2026, 8:27 a.m. |
Created at: April 10, 2026, 12:04 p.m.