Triple
T12031774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginie Ledoyen |
E286429
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | 8 Women |
E796619
|
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: 8 Women | Statement: [Virginie Ledoyen, appearedIn, 8 Women]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 8 Women Context triple: [Virginie Ledoyen, appearedIn, 8 Women]
-
A.
8 Women
chosen
8 Women is a French musical comedy-mystery film that blends stylized theatrics, dark humor, and an ensemble cast of prominent actresses in a whodunit set in the 1950s.
-
B.
3 Women
3 Women is a 1977 psychological drama film directed by Robert Altman that explores identity, personality shifts, and female relationships in a surreal, dreamlike small-town setting.
-
C.
99 Women
99 Women is a 1969 women-in-prison exploitation film, produced by Harry Alan Towers and directed by Jesús Franco, known for its controversial mix of sex, violence, and social commentary.
-
D.
Women
"Women" is a semi-autobiographical novel by Charles Bukowski that follows his hard-drinking alter ego Henry Chinaski through a series of raw, often chaotic relationships with various women.
-
E.
The Women’s
The Women’s is a major specialist public hospital in Melbourne, Australia, dedicated to women’s health, maternity, and newborn care.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903f24490819092ec911d6ed8e24b |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f646423c819088575a7032e6a9a3 |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:47 p.m.