Triple
T12313881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telê Santana |
E293548
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Mestre Telê
Mestre Telê is the revered Brazilian football coach Telê Santana, celebrated for leading some of Brazil’s most attractive and attacking teams, including the iconic 1982 World Cup side.
|
E976506
|
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: Mestre Telê | Statement: [Telê Santana, nickname, Mestre Telê]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mestre Telê Context triple: [Telê Santana, nickname, Mestre Telê]
-
A.
Mestre
Mestre is the mainland district of Venice, Italy, serving as a major residential, commercial, and transportation hub connected to the historic island city across the Venetian Lagoon.
-
B.
Tadeu
Tadeu is a given name, primarily used in Portuguese-speaking countries, that is a variant of the name Tadeusz.
-
C.
Doutor Ricardo
Doutor Ricardo is a small municipality in the state of Rio Grande do Sul in southern Brazil.
-
D.
Choque-Rei
Choque-Rei is the traditional and fiercely contested football rivalry between Brazilian clubs São Paulo FC and Palmeiras.
-
E.
Damião
Damião is a Portuguese given name, equivalent to Damian, commonly used in Lusophone countries.
- 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: Mestre Telê Triple: [Telê Santana, nickname, Mestre Telê]
Generated description
Mestre Telê is the revered Brazilian football coach Telê Santana, celebrated for leading some of Brazil’s most attractive and attacking teams, including the iconic 1982 World Cup side.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mestre Telê Target entity description: Mestre Telê is the revered Brazilian football coach Telê Santana, celebrated for leading some of Brazil’s most attractive and attacking teams, including the iconic 1982 World Cup side.
-
A.
Mestre
Mestre is the mainland district of Venice, Italy, serving as a major residential, commercial, and transportation hub connected to the historic island city across the Venetian Lagoon.
-
B.
Tadeu
Tadeu is a given name, primarily used in Portuguese-speaking countries, that is a variant of the name Tadeusz.
-
C.
Doutor Ricardo
Doutor Ricardo is a small municipality in the state of Rio Grande do Sul in southern Brazil.
-
D.
Choque-Rei
Choque-Rei is the traditional and fiercely contested football rivalry between Brazilian clubs São Paulo FC and Palmeiras.
-
E.
Damião
Damião is a Portuguese given name, equivalent to Damian, commonly used in Lusophone countries.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f03d3c88190baedffb83465bff8 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e86d45881909a9a3c09df0b78f1 |
completed | May 2, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_69f622a646c481908164ae5387625bb4 |
completed | May 2, 2026, 4:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f623f5aa608190bce3e62e08077216 |
completed | May 2, 2026, 4:19 p.m. |
Created at: April 8, 2026, 9:53 p.m.