Triple
T22301109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Mauban |
E551257
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Maria Mauban |
—
|
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: Maria Mauban | Statement: [Maria Mauban, name, Maria Mauban]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Mauban Context triple: [Maria Mauban, name, Maria Mauban]
-
A.
Maria Mauban
chosen
Maria Mauban was a French actress known for her roles in European cinema of the 1940s and 1950s, including notable performances in Italian neorealist and French films.
-
B.
Juanita Vanoy
Juanita Vanoy is a former model and Chicago-based real estate professional best known as the ex-wife of basketball legend Michael Jordan.
-
C.
Alaia-Mai Humes
Alaia-Mai Humes is the daughter of British singer and television presenter Rochelle Humes and often appears in UK media alongside her family.
-
D.
Marlene Mathias
Marlene Mathias is known as the daughter of American Olympic decathlon champion and politician Bob Mathias.
-
E.
Jacqueline Cambas
Jacqueline Cambas is a film editor known for her work on the movie "Now and Then."
- 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157245ee481909a7a3397de3ae355 |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:41 p.m.