Triple
T13664415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaguares de Chiapas |
E327078
|
entity |
| Predicate | notablePlayer |
P304
|
FINISHED |
| Object |
Danilinho
Danilinho is a Brazilian attacking midfielder known for his pace and dribbling, who made a significant impact in Mexican football, particularly in Liga MX.
|
E1053485
|
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: Danilinho | Statement: [Jaguares de Chiapas, notablePlayer, Danilinho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danilinho Context triple: [Jaguares de Chiapas, notablePlayer, Danilinho]
-
A.
Tadeu
Tadeu is a given name, primarily used in Portuguese-speaking countries, that is a variant of the name Tadeusz.
-
B.
Tostão
Tostão is a legendary Brazilian forward who starred alongside Pelé in Brazil’s iconic 1970 World Cup–winning team and is regarded as one of the country’s greatest footballers.
-
C.
Valtinho
Valtinho is a Portuguese diminutive form of the given name Valter, commonly used as an affectionate nickname.
-
D.
Piquinho
Piquinho is the prominent summit cone at the top of Mount Pico in the Azores, known as the highest point in Portugal.
-
E.
Vascão
Vascão is a popular nickname for the Brazilian football club CR Vasco da Gama, reflecting the team’s large, passionate fanbase and historic status in Rio de Janeiro football.
- 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: Danilinho Triple: [Jaguares de Chiapas, notablePlayer, Danilinho]
Generated description
Danilinho is a Brazilian attacking midfielder known for his pace and dribbling, who made a significant impact in Mexican football, particularly in Liga MX.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Danilinho Target entity description: Danilinho is a Brazilian attacking midfielder known for his pace and dribbling, who made a significant impact in Mexican football, particularly in Liga MX.
-
A.
Tadeu
Tadeu is a given name, primarily used in Portuguese-speaking countries, that is a variant of the name Tadeusz.
-
B.
Tostão
Tostão is a legendary Brazilian forward who starred alongside Pelé in Brazil’s iconic 1970 World Cup–winning team and is regarded as one of the country’s greatest footballers.
-
C.
Valtinho
Valtinho is a Portuguese diminutive form of the given name Valter, commonly used as an affectionate nickname.
-
D.
Piquinho
Piquinho is the prominent summit cone at the top of Mount Pico in the Azores, known as the highest point in Portugal.
-
E.
Vascão
Vascão is a popular nickname for the Brazilian football club CR Vasco da Gama, reflecting the team’s large, passionate fanbase and historic status in Rio de Janeiro football.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc622a07c81909ef7fb55e719dd9a |
completed | April 12, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78b0ac4c88190ab6f753c6847eb6e |
completed | May 3, 2026, 5:51 p.m. |
| NEDg | Description generation | batch_69f78cdf1a74819087b0370060ddfa99 |
completed | May 3, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f78e00007c81909007a751fd4625c2 |
completed | May 3, 2026, 6:03 p.m. |
Created at: April 9, 2026, 9:52 p.m.