Triple
T6359674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Céline |
E143077
|
entity |
| Predicate | orthographicForm |
P2203
|
FINISHED |
| Object | Céline |
E143077
|
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: Céline | Statement: [Céline, orthographicForm, Céline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Céline Context triple: [Céline, orthographicForm, Céline]
-
A.
Céline
chosen
Céline is the French given name of internationally renowned Canadian singer Céline Dion.
-
B.
Celine
Celine is a French luxury fashion house known for its minimalist, modern designs in ready-to-wear, leather goods, and accessories.
-
C.
Cécile
Cécile is the sensitive and central protagonist of the French film "Cible émouvante," around whom the story’s emotional and narrative developments revolve.
-
D.
Mademoiselle Lanoire
Mademoiselle Lanoire is an alias used by Cosette, the central female character in Victor Hugo’s novel "Les Misérables."
-
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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067f8758081909c5ce40abf57dd2c |
completed | March 22, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c63869ef148190816b152f2724de49 |
completed | March 27, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:32 p.m.