Triple
T21213415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Maior |
E522774
|
entity |
| Predicate | demographicsLabel |
P2263
|
FINISHED |
| Object |
Rio-maiorense
Rio-maiorense is the demonym for inhabitants or natives of the Portuguese municipality of Rio Maior.
|
E1472603
|
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: Rio-maiorense | Statement: [Rio Maior, demographicsLabel, Rio-maiorense]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio-maiorense Context triple: [Rio Maior, demographicsLabel, Rio-maiorense]
-
A.
Caicó
Caicó is a municipality in the interior of Rio Grande do Norte, Brazil, known for its strong cultural traditions, especially its famous religious festivals and regional cuisine.
-
B.
Sumidouro
Sumidouro is a small municipality in the mountainous Região Serrana of Rio de Janeiro state in southeastern Brazil, known for its rural landscapes and cooler climate.
-
C.
Mauá
Mauá is an industrial and residential city located in the metropolitan region of São Paulo, Brazil.
-
D.
Ananindeua
Ananindeua is a major urban and industrial city in northern Brazil, located in the state of Pará within the Amazon region.
-
E.
Marromeu
Marromeu is a town and district in central Mozambique known for its location along the Zambezi River and proximity to the Marromeu Buffalo Reserve.
- 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: Rio-maiorense Triple: [Rio Maior, demographicsLabel, Rio-maiorense]
Generated description
Rio-maiorense is the demonym for inhabitants or natives of the Portuguese municipality of Rio Maior.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rio-maiorense Target entity description: Rio-maiorense is the demonym for inhabitants or natives of the Portuguese municipality of Rio Maior.
-
A.
Caicó
Caicó is a municipality in the interior of Rio Grande do Norte, Brazil, known for its strong cultural traditions, especially its famous religious festivals and regional cuisine.
-
B.
Sumidouro
Sumidouro is a small municipality in the mountainous Região Serrana of Rio de Janeiro state in southeastern Brazil, known for its rural landscapes and cooler climate.
-
C.
Mauá
Mauá is an industrial and residential city located in the metropolitan region of São Paulo, Brazil.
-
D.
Ananindeua
Ananindeua is a major urban and industrial city in northern Brazil, located in the state of Pará within the Amazon region.
-
E.
Marromeu
Marromeu is a town and district in central Mozambique known for its location along the Zambezi River and proximity to the Marromeu Buffalo Reserve.
- 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7347088488190aa764b3f4bbac44d |
completed | April 21, 2026, 8:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a097ed6e6288190a6c0a10338458117 |
completed | May 17, 2026, 8:39 a.m. |
| NEDg | Description generation | batch_6a097ff28ed0819081cea66e9ea5eaa2 |
completed | May 17, 2026, 8:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0981477234819093bc90f3578ddccf |
completed | May 17, 2026, 8:50 a.m. |
Created at: April 16, 2026, 3:38 p.m.