Triple
T17405974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humbert |
E423214
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Humberto |
—
|
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: Humberto | Statement: [Humbert, hasVariant, Humberto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Humberto Context triple: [Humbert, hasVariant, Humberto]
-
A.
Humberto
chosen
Humberto is a masculine given name of Spanish and Portuguese origin, commonly used in Iberian and Latin American countries.
-
B.
Ernesto
Ernesto is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
C.
Gustavo
Gustavo is a masculine given name commonly used in Spanish- and Portuguese-speaking countries, equivalent to the name Gustaf.
-
D.
Tulio
Tulio is one of the two witty con-artist protagonists in the animated adventure film "The Road to El Dorado."
-
E.
Jorge
Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b0750688190bb123634d7c7273e |
completed | April 19, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:45 a.m.