Triple
T2560970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Brazilians |
E57240
|
entity |
| Predicate | notableCity |
P2813
|
FINISHED |
| Object |
Lajeado
Lajeado is a city in southern Brazil known for its strong German-Brazilian cultural heritage and traditions.
|
E281396
|
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: Lajeado | Statement: [German Brazilians, notableCity, Lajeado]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lajeado Context triple: [German Brazilians, notableCity, Lajeado]
-
A.
Caxangá
Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
-
B.
Estância
Estância is a municipality in the Brazilian state of Sergipe, known for its coastal location and traditional June festivals.
-
C.
Campoalegre
Campoalegre is a municipality and town in southwestern Colombia, located in the Huila Department and known for its agricultural production.
-
D.
Nipomo
Nipomo is a small unincorporated community in California’s Central Coast region, known for its agricultural roots and proximity to the Pacific Ocean in southern San Luis Obispo County.
-
E.
Pau dos Ferros
Pau dos Ferros is a municipality in the interior of Brazil’s Rio Grande do Norte state, known as a regional commercial and educational hub in the Alto Oeste Potiguar region.
- 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: Lajeado Triple: [German Brazilians, notableCity, Lajeado]
Generated description
Lajeado is a city in southern Brazil known for its strong German-Brazilian cultural heritage and traditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lajeado Target entity description: Lajeado is a city in southern Brazil known for its strong German-Brazilian cultural heritage and traditions.
-
A.
Caxangá
Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
-
B.
Estância
Estância is a municipality in the Brazilian state of Sergipe, known for its coastal location and traditional June festivals.
-
C.
Campoalegre
Campoalegre is a municipality and town in southwestern Colombia, located in the Huila Department and known for its agricultural production.
-
D.
Nipomo
Nipomo is a small unincorporated community in California’s Central Coast region, known for its agricultural roots and proximity to the Pacific Ocean in southern San Luis Obispo County.
-
E.
Pau dos Ferros
Pau dos Ferros is a municipality in the interior of Brazil’s Rio Grande do Norte state, known as a regional commercial and educational hub in the Alto Oeste Potiguar region.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd334b69481908a6f2c0b41550ce9 |
completed | March 7, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83a4f6788190be268076838711df |
completed | March 10, 2026, 2:36 a.m. |
| NEDg | Description generation | batch_69af84d26eb48190b982441a0a63ccda |
completed | March 10, 2026, 2:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af858561f48190b7a2863d733a1b13 |
completed | March 10, 2026, 2:44 a.m. |
Created at: March 6, 2026, 9:48 p.m.