Triple
T900145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Róbert |
E19427
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Roberto |
E26746
|
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: Roberto | Statement: [Róbert, relatedName, Roberto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roberto Context triple: [Róbert, relatedName, Roberto]
-
A.
Roberto
chosen
Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
-
B.
Alberto
Alberto is a masculine given name common in Romance-language countries, derived from the Germanic name Albert and sharing its meaning of "noble" or "bright."
-
C.
Eugenio
Eugenio is a masculine given name of Greek origin, commonly used in Spanish- and Italian-speaking countries.
-
D.
Paolo
Paolo is the Italian form of the given name Paul, commonly used in Italy and other Italian-speaking communities.
-
E.
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.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad42ecac81909f8bc554d2fe0363 |
completed | March 1, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4bfe2ce081908c358689ec2c58e6 |
completed | March 7, 2026, 4:02 p.m. |
Created at: March 1, 2026, 7:39 p.m.