Triple
T15042799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mireille |
E378642
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Mireille |
E378642
|
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: Mireille | Statement: [Mireille, mainCharacter, Mireille]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mireille Context triple: [Mireille, mainCharacter, Mireille]
-
A.
Mireille
chosen
Mireille is a five-act French opera by Charles Gounod, based on Frédéric Mistral’s Provençal poem "Mirèio."
-
B.
Gisèle
Gisèle is a feminine given name of French origin, commonly used in Francophone countries and beyond.
-
C.
Michèle
Michèle is a feminine given name of French origin, commonly used in French-speaking countries.
-
D.
Mariette Lydis
Mariette Lydis was an Austrian-Argentine painter and illustrator known for her expressive, often melancholic depictions of women and marginalized figures in early 20th-century art.
-
E.
Micheline
Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82f73208190bb55fa6b20074e27 |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef603b788190ad747d73af2363d4 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3 a.m.