Triple
T16606361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germano Celant |
E403455
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Germano |
E309446
|
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: Germano | Statement: [Germano Celant, givenName, Germano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Germano Context triple: [Germano Celant, givenName, Germano]
-
A.
Germano
chosen
Germano is a masculine given name and surname of Romance-language origin, cognate with the French name Germain.
-
B.
Tedesco
Tedesco is an Italian-origin surname borne by various notable individuals in fields such as politics, sports, and the arts.
-
C.
Latiano
Latiano is a town and comune in the Apulia region of southern Italy, known for its historic center and agricultural traditions.
-
D.
Germán
Germán is a Spanish given name, commonly used in Spanish-speaking countries and derived from the same roots as the name Germain.
-
E.
Talian
Talian is a Brazilian variety of Venetian-based Italian dialects spoken mainly in southern Brazil, particularly within Italian immigrant communities.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36091de048190b40aa42b1a0681cc |
completed | April 18, 2026, 10:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0075a8a6248190a9e2bb469d821c66 |
completed | May 10, 2026, 12:10 p.m. |
Created at: April 10, 2026, 5:17 a.m.