Triple
T22094925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tardi |
E546000
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Tardi |
—
|
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: Tardi | Statement: [Tardi, familyName, Tardi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tardi Context triple: [Tardi, familyName, Tardi]
-
A.
Tardi
chosen
Tardi is a renowned French cartoonist and graphic novelist best known for his dark, expressive artwork and critically acclaimed bandes dessinées such as the "Adèle Blanc-Sec" series and his World War I-themed works.
-
B.
Valerio Bonelli
Valerio Bonelli is a film editor known for his work on acclaimed movies such as "Philomena."
-
C.
Hugo Pratt
Hugo Pratt was an influential Italian comic book creator best known for his atmospheric, adventure-driven graphic novels, particularly the Corto Maltese series.
-
D.
Dore
Dore is a suburban village on the southwestern edge of Sheffield, England, known for its affluent residential character and proximity to the Peak District.
-
E.
Dore
The Dore is a river in central France that flows through the Massif Central before joining the Allier.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e82c1481908701f255b834f192 |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.