Triple
T190126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul |
E3700
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Paulo |
E30439
|
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: Paulo | Statement: [Paul, hasVariant, Paulo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paulo Context triple: [Paul, hasVariant, Paulo]
-
A.
Paolo
Paolo is the Italian form of the given name Paul, commonly used in Italy and other Italian-speaking communities.
-
B.
Pablo
chosen
Pablo is a given name, especially common in Spanish-speaking countries, that corresponds to the English name Paul.
-
C.
Roberto
Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
-
D.
Jorge
Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
-
E.
Tiago
Tiago is a masculine given name commonly used in Portuguese-speaking countries, often considered a variant of the name James.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594c385481909e1e088e45c460a4 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a36958f6488190872ccf3c318a3cfa |
completed | Feb. 28, 2026, 10:16 p.m. |
Created at: Feb. 28, 2026, 2:41 a.m.