Triple
T12424724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Formula |
E296867
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Marthe Keller |
E213946
|
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: Marthe Keller | Statement: [The Formula, starring, Marthe Keller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marthe Keller Context triple: [The Formula, starring, Marthe Keller]
-
A.
Marthe Keller
chosen
Marthe Keller is a Swiss actress and former opera director known for her international film career, including prominent roles in 1970s Hollywood thrillers and European cinema.
-
B.
Marthe
Marthe is a feminine given name, commonly used in French and other European languages, that is a variant of the name Martha.
-
C.
Marthe Poncin
Marthe Poncin was a film editor known for her work on French cinema, including editing the classic film "Hôtel du Nord."
-
D.
Berthe Belluot
Berthe Belluot was the wife of French statesman Félix Faure, who served as President of France in the late 19th century.
-
E.
Marie Pillet
Marie Pillet was a French actress and activist, best known to many as the mother of filmmaker and actress Julie Delpy.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d7b6bd08190b30beba393a5b1e7 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f0265fc81909a6288d11b78c2f9 |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:55 p.m.