Triple
T11703260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serra Gaúcha |
E278175
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object |
Santa Tereza
Santa Tereza is a small wine-producing town in Brazil’s Serra Gaúcha region, known for its Italian heritage and scenic mountain landscapes.
|
E941803
|
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: Santa Tereza | Statement: [Serra Gaúcha, hasMajorTown, Santa Tereza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Tereza Context triple: [Serra Gaúcha, hasMajorTown, Santa Tereza]
-
A.
Santa Teresa
Santa Teresa is a historic, bohemian hilltop neighborhood in Rio de Janeiro known for its winding streets, colonial mansions, and vibrant arts scene.
-
B.
Santa Teresa Cora
Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
-
C.
Santa Isabel
Santa Isabel is a supermarket chain in Latin America operated under the retail group Cencosud.
-
D.
Santa Isabel
Santa Isabel was the colonial capital city of Spanish Equatorial Guinea, serving as the administrative and political center during Spanish rule.
-
E.
Santa Isabel
Santa Isabel was a Spanish expedition ship associated with the Santa Cruz colony during the era of New World exploration.
- 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: Santa Tereza Triple: [Serra Gaúcha, hasMajorTown, Santa Tereza]
Generated description
Santa Tereza is a small wine-producing town in Brazil’s Serra Gaúcha region, known for its Italian heritage and scenic mountain landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santa Tereza Target entity description: Santa Tereza is a small wine-producing town in Brazil’s Serra Gaúcha region, known for its Italian heritage and scenic mountain landscapes.
-
A.
Santa Teresa
Santa Teresa is a historic, bohemian hilltop neighborhood in Rio de Janeiro known for its winding streets, colonial mansions, and vibrant arts scene.
-
B.
Santa Teresa Cora
Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
-
C.
Santa Isabel
Santa Isabel was a Spanish expedition ship associated with the Santa Cruz colony during the era of New World exploration.
-
D.
Santa Isabel
Santa Isabel is a supermarket chain in Latin America operated under the retail group Cencosud.
-
E.
Santa Isabel
Santa Isabel was the colonial capital city of Spanish Equatorial Guinea, serving as the administrative and political center during Spanish rule.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49b1080819096593733ee48a187 |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef83525ae081909ee6f3fbb5d37dd7 |
completed | April 27, 2026, 3:40 p.m. |
| NEDg | Description generation | batch_69ef9b673120819097b542bb9a8f8bdb |
completed | April 27, 2026, 5:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69efd683366881909dd9621e7c57d0be |
completed | April 27, 2026, 9:34 p.m. |
Created at: April 8, 2026, 9:40 p.m.