Triple
T3249773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Storm |
E68147
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Bobinôt |
E340865
|
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: Bobinôt | Statement: [The Storm, character, Bobinôt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bobinôt Context triple: [The Storm, character, Bobinôt]
-
A.
Bobinôt
chosen
Bobinôt is a hardworking, plainspoken Cajun farmer in Kate Chopin’s fiction, best known as the devoted but socially awkward suitor and later husband of Calixta.
-
B.
Fernandel
Fernandel was a beloved French comic actor and singer, famed for his expressive face and roles in classic mid-20th-century films such as the Don Camillo series.
-
C.
Baron Hector Hulot
Baron Hector Hulot is a central figure in Honoré de Balzac’s novel "La Cousine Bette," portrayed as a once-distinguished but morally weak and womanizing government official whose excesses bring ruin upon his family.
-
D.
Douzy
Douzy is a small commune in the Ardennes department of northern France, known for its rural character and cross-border ties, including a town twinning with Kaiserslautern in Germany.
-
E.
Marcel
Marcel is a masculine given name of French origin, commonly used in various European 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28eb55734819093f470caacc3e29c |
completed | March 12, 2026, 10 a.m. |
Created at: March 8, 2026, 3:09 p.m.