Triple
T21181199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nacional |
E521953
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Nacional |
—
|
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: Nacional | Statement: [Nacional, shortName, Nacional]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nacional Context triple: [Nacional, shortName, Nacional]
-
A.
Nacional
chosen
Nacional is a Portuguese professional football club based in Funchal, Madeira, known for competing in the country’s top leagues and developing notable players.
-
B.
Nacional
Nacional is a character in the 1922 silent drama film "Blood and Sand," which centers on the rise and fall of a celebrated Spanish bullfighter.
-
C.
Nacional
Nacional is a news section of the Colombian newspaper El Espectador that focuses on national-level events and issues.
-
D.
Nacional
Nacional is a prominent Uruguayan football club based in Montevideo, known as one of the country's most successful and historic teams.
-
E.
Nationale
Nationale is a French national-level rugby union competition that forms part of the country’s professional and semi-professional league structure.
- 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_69e0b50ef1d48190b063aa342667df22 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7301da0ac8190a965fee7b6d845e7 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 3:01 p.m.