Triple
T1677833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanche |
E36272
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Bianca |
E77294
|
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: Bianca | Statement: [Blanche, hasVariant, Bianca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bianca Context triple: [Blanche, hasVariant, Bianca]
-
A.
Bianca
chosen
Bianca is a key supporting character in the "Creed" film series, a musician and love interest of Adonis Creed who plays a central role in his personal life and emotional journey.
-
B.
Rachele
Rachele is an Italian given name, notably borne by Rachele Mussolini, the wife of dictator Benito Mussolini.
-
C.
Luisa
Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
-
D.
Felicia
Felicia is a feminine given name of Latin origin meaning "happy" or "fortunate," used in various cultures around the world.
-
E.
Silvia
Silvia is a feminine given name used in various languages, often associated with the Latin word for "forest" or "woods."
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa625f7e1081909c3c4fe76625783a |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb96d12481908f8d7d5c9f1f103f |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 4, 2026, 7:29 p.m.