Triple
T17578674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcello Gandini |
E428139
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marcello |
E88497
|
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: Marcello | Statement: [Marcello Gandini, givenName, Marcello]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcello Context triple: [Marcello Gandini, givenName, Marcello]
-
A.
Marcello
chosen
Marcello is a masculine given name of Italian origin, commonly used in Italy and other Romance-language countries.
-
B.
Stelio
Stelio is the given name of Stelio Frati, an Italian aeronautical engineer and aircraft designer renowned for creating light, high-performance airplanes.
-
C.
Luciano
Luciano is a masculine given name of Italian origin, famously borne by the renowned operatic tenor Luciano Pavarotti.
-
D.
Renzo
Renzo is the given name of Renzo Piano, the renowned Italian architect known for designing landmark buildings such as the Centre Pompidou in Paris and The Shard in London.
-
E.
Stefano
Stefano is the Italian given name corresponding to the Hungarian name István, commonly used as a male first name in Italy.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463cb40088190b726f2c026358cf2 |
completed | April 19, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01e81178dc8190926193196ba01f41 |
completed | May 11, 2026, 2:30 p.m. |
Created at: April 10, 2026, 5:50 a.m.