Triple
T9586012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maury |
E231291
|
entity |
| Predicate | sharesOriginWith |
P3438
|
FINISHED |
| Object | Mauro |
E809080
|
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: Mauro | Statement: [Maury, sharesOriginWith, Mauro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mauro Context triple: [Maury, sharesOriginWith, Mauro]
-
A.
Mauro
chosen
Mauro is a masculine given name, common in Italian and Spanish-speaking countries, derived from the Latin name Maurus.
-
B.
Aroldo
Aroldo is a lesser-known opera by Italian composer Giuseppe Verdi, adapted from his earlier work Stiffelio and set in medieval England and Scotland.
-
C.
Silvano
Silvano is an Italian given name, related to Silvio, traditionally associated with the Latin name Silvanus meaning "of the forest" or "woodland."
-
D.
Roberto
Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
-
E.
Marcelo
Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
- 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_69ca848161688190a68d514a0a9d5129 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99edc2c08190b67b40f6214d46f1 |
completed | April 1, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d189ef34c48190974a1a4ca6943a87 |
completed | April 4, 2026, 10 p.m. |
Created at: March 30, 2026, 8:06 p.m.