Triple
T8635160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fla-Flu |
E204505
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Fla x Flu |
E204505
|
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: Fla x Flu | Statement: [Fla-Flu, alsoKnownAs, Fla x Flu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fla x Flu Context triple: [Fla-Flu, alsoKnownAs, Fla x Flu]
-
A.
Fla-Flu
chosen
Fla-Flu is one of Brazil’s most famous and historic football rivalries, contested between Rio de Janeiro clubs Flamengo and Fluminense.
-
B.
Fluzão
Fluzão is a popular nickname for Fluminense Football Club, one of Brazil’s traditional Rio de Janeiro–based football teams.
-
C.
Lit Up
"Lit Up" is a song by the American rock band Alligator.
-
D.
The Fever Van
The Fever Van is a painting by British artist L. S. Lowry that depicts an urban street scene centered on an ambulance-like "fever van," capturing the atmosphere of working-class life in industrial England.
-
E.
Sticky Fingaz
Sticky Fingaz is an American rapper and actor best known as a member of the hardcore hip hop group Onyx and for his roles in film and television.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc475fb9dc8190bd0d6e5edd05ea79 |
completed | March 31, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebc1b330c81909ff8a6806401dfd1 |
completed | April 2, 2026, 6:57 p.m. |
Created at: March 30, 2026, 6:27 p.m.