Triple
T17082358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcellino |
E414504
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Marcello (given name) |
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 (given name) | Statement: [Marcellino, hasRelatedName, Marcello (given name)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcello (given name) Context triple: [Marcellino, hasRelatedName, Marcello (given name)]
-
A.
Marcello
chosen
Marcello is a masculine given name of Italian origin, commonly used in Italy and other Romance-language countries.
-
B.
Gianfranco
Gianfranco is an Italian masculine given name commonly associated with notable figures in fashion, sports, and the arts.
-
C.
Patrizio
Patrizio is an Italian given name commonly used for men, notably borne by figures such as fashion executive Patrizio Bertelli.
-
D.
Luciano
Luciano is a masculine given name of Italian origin, famously borne by the renowned operatic tenor Luciano Pavarotti.
-
E.
Gaetano
Gaetano is an Italian given name, historically notable as the birth name of Saint Cajetan, a prominent 16th-century Catholic priest and reformer.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe408d48190b4f52c2102eae7c2 |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ee416c4819087e7ae0ead47867a |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:35 a.m.