Triple
T11942151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nunes |
E284202
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Nunez |
E712509
|
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: Nunez | Statement: [Nunes, hasVariant, Nunez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nunez Context triple: [Nunes, hasVariant, Nunez]
-
A.
Núñez
chosen
Núñez is a residential neighborhood in northern Buenos Aires, Argentina, best known in sports for hosting River Plate’s Monumental stadium.
-
B.
Quiñonez
Quiñonez is the surname of actor Tony Revolori, known for his role in "The Grand Budapest Hotel."
-
C.
Sosa
Sosa is a Spanish-origin surname most famously associated with former Major League Baseball slugger Sammy Sosa.
-
D.
Balderas
Balderas is a major Mexico City Metro station known for its central location and high passenger traffic.
-
E.
Velasco
Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90342bb908190a019ac91a2b82f3d |
completed | April 10, 2026, 2:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f471ba7fd88190909596e6e01e8714 |
completed | May 1, 2026, 9:26 a.m. |
Created at: April 8, 2026, 9:45 p.m.