Triple
T4752878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa Paradis |
E105518
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Vanessa Paradis |
E105518
|
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: Vanessa Paradis | Statement: [Vanessa Paradis, name, Vanessa Paradis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vanessa Paradis Context triple: [Vanessa Paradis, name, Vanessa Paradis]
-
A.
Vanessa Paradis
chosen
Vanessa Paradis is a French singer, actress, and model who gained fame as a teen pop star and later for her long-term relationship with actor Johnny Depp.
-
B.
Melanie Thierry
Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
-
C.
Sylvie Vartan
Sylvie Vartan is a Bulgarian-born French pop singer and actress who became one of France’s most popular yé-yé idols in the 1960s.
-
D.
Jane Birkin
Jane Birkin was an English-French actress and singer renowned for her artistic partnership with Serge Gainsbourg and her enduring influence on fashion and popular culture.
-
E.
Brigitte Marie-Claude Trogneux
Brigitte Marie-Claude Trogneux is a French former teacher and the First Lady of France, married to President Emmanuel Macron.
- 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_69bd43f07fa48190954317d01600994a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64e5fba88190b1f28d1b0eed3f8e |
completed | March 20, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a5ddf088190892d31275adb39ba |
completed | March 21, 2026, 6:27 a.m. |
Created at: March 20, 2026, 1:20 p.m.