Triple
T20287158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcio |
E509914
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Marcio (with accent: Márcio) |
—
|
NE NERFINISHED |
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: Marcio (with accent: Márcio) | Statement: [Marcio, hasRelatedName, Marcio (with accent: Márcio)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcio (with accent: Márcio) Context triple: [Marcio, hasRelatedName, Marcio (with accent: Márcio)]
-
A.
Marcio
chosen
Marcio is a masculine given name commonly used in Portuguese- and Spanish-speaking countries, derived from the Latin name Marcius.
-
B.
Marcos Evangelista de Morais
Marcos Evangelista de Morais, better known as Cafu, is a retired Brazilian footballer widely regarded as one of the greatest right-backs in the history of the sport.
-
C.
Brian Marcos
Brian Marcos is the son of Dominic Toretto in the Fast & Furious film franchise.
-
D.
Fabrício
Fabrício is the given name of Fabrício Werdum, a Brazilian mixed martial artist and former UFC heavyweight champion.
-
E.
Márcio Thomaz Bastos
Márcio Thomaz Bastos was a prominent Brazilian lawyer and politician who served as Brazil’s Minister of Justice in the early 2000s, playing a key role in legal and public security reforms.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e676931fe08190b278d829a745701f |
completed | April 20, 2026, 6:55 p.m. |
Created at: April 16, 2026, 11:07 a.m.