Triple
T12619212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurent Blanc |
E301335
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Blanc |
E55361
|
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: Blanc | Statement: [Laurent Blanc, familyName, Blanc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blanc Context triple: [Laurent Blanc, familyName, Blanc]
-
A.
Blanc
chosen
Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
-
B.
Bianco
Bianco is an Italian surname commonly associated with individuals of Italian heritage, including the artist Enrico Bianco.
-
C.
Blanco
Blanco is a Spanish-language surname most notably associated with Mexican football legend and politician Cuauhtémoc Blanco.
-
D.
White’s
White’s is one of London’s oldest and most exclusive gentlemen’s clubs, renowned for its aristocratic membership and historic premises in St James’s.
-
E.
Witte
Witte is a surname most notably associated with Edwin E. Witte, an American economist often called the “father of Social Security” for his key role in shaping U.S. social welfare policy.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d960c75c9c819092265ebc2b39f21d |
completed | April 10, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ed507988190b9d46586f3c3584c |
completed | May 2, 2026, 8:30 p.m. |
Created at: April 9, 2026, 5:13 p.m.