Triple
T14285250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matteo |
E354153
|
entity |
| Predicate | variantForm |
P4680
|
FINISHED |
| Object | Mattia |
E1065142
|
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: Mattia | Statement: [Matteo, variantForm, Mattia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mattia Context triple: [Matteo, variantForm, Mattia]
-
A.
Matteo
Matteo is the Italian given name equivalent to Matthew, commonly used in Italy and other Italian-speaking communities.
-
B.
Mateo
Mateo is a masculine given name of Spanish origin, commonly used in Spanish-speaking countries and derived from the Hebrew name Matthew, meaning "gift of God."
-
C.
Mattia Dessi
Mattia Dessi is an Italian former model and television personality best known as the husband of actress and model Brigitte Nielsen.
-
D.
Tommaso
Tommaso is the given name of Thomas Francis, Prince of Carignano, a 17th-century Italian nobleman of the House of Savoy.
-
E.
Mattia Verazi
chosen
Mattia Verazi was an 18th-century Italian librettist known for his innovative and often reformist opera texts, including the libretto for Antonio Salieri’s "Europa riconosciuta."
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de697ef40c8190bea37724b28c2e99 |
completed | April 14, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c31654c81908f53d4c21e255afb |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:10 a.m.