Triple
T7426481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Bull Bragantino |
E171379
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object |
Massa Bruta
Massa Bruta is the popular nickname of Brazilian football club Red Bull Bragantino, reflecting its strong and combative playing style.
|
E663391
|
NE FINISHED |
How this triple was built (4 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: Massa Bruta | Statement: [Red Bull Bragantino, hasNickname, Massa Bruta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Massa Bruta Context triple: [Red Bull Bragantino, hasNickname, Massa Bruta]
-
A.
Massa
Massa is a small coastal town in southern Morocco known for its proximity to the Souss-Massa National Park and its traditional Berber culture.
-
B.
Massa
Massa is a historic city in northwestern Tuscany, Italy, known for its marble industry and proximity to the Apuan Alps and the Tyrrhenian coast.
-
C.
Massa
Massa is a biblical figure listed among the descendants of Ishmael in the Hebrew Bible.
-
D.
Peso da Régua
Peso da Régua is a Portuguese city in the Douro Valley known as a key hub for the region’s famous port wine production and river tourism.
-
E.
Roda de Ter
Roda de Ter is a small municipality in the Osona comarca of Catalonia, Spain, known for its historical textile industry and riverside setting along the Ter River.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Massa Bruta Triple: [Red Bull Bragantino, hasNickname, Massa Bruta]
Generated description
Massa Bruta is the popular nickname of Brazilian football club Red Bull Bragantino, reflecting its strong and combative playing style.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Massa Bruta Target entity description: Massa Bruta is the popular nickname of Brazilian football club Red Bull Bragantino, reflecting its strong and combative playing style.
-
A.
Massa
Massa is a small coastal town in southern Morocco known for its proximity to the Souss-Massa National Park and its traditional Berber culture.
-
B.
Massa
Massa is a historic city in northwestern Tuscany, Italy, known for its marble industry and proximity to the Apuan Alps and the Tyrrhenian coast.
-
C.
Massa
Massa is a biblical figure listed among the descendants of Ishmael in the Hebrew Bible.
-
D.
Peso da Régua
Peso da Régua is a Portuguese city in the Douro Valley known as a key hub for the region’s famous port wine production and river tourism.
-
E.
Roda de Ter
Roda de Ter is a small municipality in the Osona comarca of Catalonia, Spain, known for its historical textile industry and riverside setting along the Ter River.
- F. None of above. chosen
Provenance (5 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3055b7881908269ab909c5a85b5 |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81f09787c819090b8be24070a7105 |
completed | March 28, 2026, 6:33 p.m. |
| NEDg | Description generation | batch_69c81fd379cc81908b52c45fddea9870 |
completed | March 28, 2026, 6:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8209b7fa48190aea45a6b21ad8de1 |
completed | March 28, 2026, 6:40 p.m. |
Created at: March 27, 2026, 3:12 p.m.