Triple
T596679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Primo Levi |
E11399
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Primo |
E11398
|
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: Primo | Statement: [Primo Levi, givenName, Primo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Primo Context triple: [Primo Levi, givenName, Primo]
-
A.
Primo
chosen
Primo is an Italian masculine given name most famously associated with the writer and Holocaust survivor Primo Levi.
-
B.
Salvator
Salvator is the Latin term traditionally used in Christian theology and liturgy to refer to Jesus Christ as the Savior.
-
C.
Mwanza
Mwanza is a major port city in northwestern Tanzania, situated on the southern shores of Lake Victoria and serving as a key commercial and transport hub for the region.
-
D.
Paolo
Paolo is the Italian form of the given name Paul, commonly used in Italy and other Italian-speaking communities.
-
E.
Riggo
Riggo is the nickname of John Riggins, a Hall of Fame NFL running back best known for his powerful rushing style with the Washington Redskins.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d2b98d08190a1c1e8659efdfd75 |
completed | March 1, 2026, 8:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a51f36ab388190a418f6d4ffe91d66 |
completed | March 2, 2026, 5:25 a.m. |
Created at: March 1, 2026, 7:35 p.m.