Triple
T22234570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cimiez Cemetery |
E549556
|
entity |
| Predicate | hasNotableBurial |
P196
|
FINISHED |
| Object | Colette |
—
|
NE NERFINISHED |
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: Colette | Statement: [Cimiez Cemetery, hasNotableBurial, Colette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colette Context triple: [Cimiez Cemetery, hasNotableBurial, Colette]
-
A.
Colette
chosen
Colette was a renowned French novelist and memoirist, celebrated for works such as "Gigi" and "Claudine" that explored female identity, sensuality, and independence.
-
B.
Colette
Colette is a 2018 biographical drama film about the French novelist Sidonie-Gabrielle Colette, chronicling her literary career and fight for creative ownership in early 20th-century Paris.
-
C.
Colette Capdevielle
Colette Capdevielle is a French politician known for her involvement in centrist and independent political movements.
-
D.
Colette Brosset
Colette Brosset was a French actress and comedian known for her work in mid-20th-century film and theater, often appearing in musical comedies and farces.
-
E.
Colette Bertier
Colette Bertier is a character in the 1932 musical romantic comedy film "One Hour with You," involved in the film’s lighthearted entanglements of love and infidelity.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf61504819093e70bee4c575d1c |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:38 p.m.