Triple
T11869603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yvette Mimieux |
E282371
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Mimieux
Mimieux is a French surname most notably associated with American actress Yvette Mimieux, known for her film and television work in the 1960s and 1970s.
|
E960067
|
NE FINISHED |
How this triple was built (4 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: Mimieux | Statement: [Yvette Mimieux, familyName, Mimieux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mimieux Context triple: [Yvette Mimieux, familyName, Mimieux]
-
A.
Noailles
Noailles is a renowned art district in Croix-des-Bouquets, Haiti, famous for its vibrant community of metal sculptors and artisans.
-
B.
Glavieux
Glavieux is a French surname most notably associated with Alain Glavieux, a prominent engineer known for his contributions to error-correcting codes.
-
C.
Boucicaut
Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
-
D.
Vauvert
Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
-
E.
Juliénas
Juliénas is a French wine appellation in the northern Beaujolais region, known for its structured, aromatic red wines primarily made from the Gamay grape.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mimieux Triple: [Yvette Mimieux, familyName, Mimieux]
Generated description
Mimieux is a French surname most notably associated with American actress Yvette Mimieux, known for her film and television work in the 1960s and 1970s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mimieux Target entity description: Mimieux is a French surname most notably associated with American actress Yvette Mimieux, known for her film and television work in the 1960s and 1970s.
-
A.
Noailles
Noailles is a renowned art district in Croix-des-Bouquets, Haiti, famous for its vibrant community of metal sculptors and artisans.
-
B.
Glavieux
Glavieux is a French surname most notably associated with Alain Glavieux, a prominent engineer known for his contributions to error-correcting codes.
-
C.
Boucicaut
Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
-
D.
Vauvert
Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
-
E.
Juliénas
Juliénas is a French wine appellation in the northern Beaujolais region, known for its structured, aromatic red wines primarily made from the Gamay grape.
- F. None of above. chosen
Provenance (5 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73c04e4819084c0b2ff8e5d2f04 |
completed | April 10, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48a4d0e908190b6465b1094373e2c |
completed | May 1, 2026, 11:11 a.m. |
| NEDg | Description generation | batch_69f48fc3baac8190af87b55164f00b26 |
completed | May 1, 2026, 11:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f495ab52788190a886f7014267f8e2 |
completed | May 1, 2026, 11:59 a.m. |
Created at: April 8, 2026, 9:43 p.m.