Triple
T2480287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noel Blanc |
E55798
|
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: [Noel Blanc, familyName, Blanc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blanc Context triple: [Noel 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.
Blanco
Blanco is a Spanish-language surname most notably associated with Mexican football legend and politician Cuauhtémoc Blanco.
-
C.
Case White
Case White was the German codename for the 1939 invasion of Poland that marked the beginning of World War II in Europe.
-
D.
Blau
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
-
E.
Biancocelesti
Biancocelesti is the traditional nickname for Italian football club S.S. Lazio, referring to the team’s white and sky-blue colors.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd160a9708190b28d2f5538ea129a |
completed | March 7, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1f8c02188190a7cf3e0531a66683 |
completed | March 9, 2026, 7:29 p.m. |
Created at: March 6, 2026, 9:45 p.m.