Triple
T5095362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrea Bocelli |
E114851
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Andrea |
E128057
|
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: Andrea | Statement: [Andrea Bocelli, givenName, Andrea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrea Context triple: [Andrea Bocelli, givenName, Andrea]
-
A.
Andrea
chosen
Andrea is the given name of the influential Italian Renaissance architect Andrea Palladio, whose classical designs shaped Western architecture.
-
B.
Rachele
Rachele is an Italian given name, notably borne by Rachele Mussolini, the wife of dictator Benito Mussolini.
-
C.
Andi
Andi is a common diminutive or nickname for the given name Andreas.
-
D.
Adrienne
Adrienne is a feminine given name of French origin, commonly used in English- and French-speaking countries.
-
E.
Andrea Ammon
Andrea Ammon is a German physician and public health expert who serves as the director of the European Centre for Disease Prevention and Control, leading EU efforts in infectious disease surveillance and response.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7563ad608190879a26a0bf07c3f6 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba7b87c08190a2581c87f965fa9f |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:40 p.m.