Triple
T10401295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Região dos Lagos |
E245151
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Araruama
Araruama is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its large saltwater lagoon and tourism.
|
E865338
|
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: Araruama | Statement: [Região dos Lagos, contains, Araruama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Araruama Context triple: [Região dos Lagos, contains, Araruama]
-
A.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
-
B.
Igarassu
Igarassu is one of Brazil’s oldest colonial towns, known for its historic churches and coastal location in the northeastern state of Pernambuco.
-
C.
Macuco
Macuco is a small municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, Brazil.
-
D.
Itapura
Itapura is a municipality in the state of São Paulo, Brazil, located on the banks of the Tietê River near its confluence with the Paraná River.
-
E.
Kungur
Kungur is a historic Russian town in Perm Krai known for its ice cave, traditional trade heritage, and role as a regional cultural center.
- 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: Araruama Triple: [Região dos Lagos, contains, Araruama]
Generated description
Araruama is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its large saltwater lagoon and tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Araruama Target entity description: Araruama is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its large saltwater lagoon and tourism.
-
A.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
-
B.
Igarassu
Igarassu is one of Brazil’s oldest colonial towns, known for its historic churches and coastal location in the northeastern state of Pernambuco.
-
C.
Macuco
Macuco is a small municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, Brazil.
-
D.
Itapura
Itapura is a municipality in the state of São Paulo, Brazil, located on the banks of the Tietê River near its confluence with the Paraná River.
-
E.
Kungur
Kungur is a historic Russian town in Perm Krai known for its ice cave, traditional trade heritage, and role as a regional cultural center.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e2f11c8190b30695cba2975544 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89f6fbc848190806d50bfad654b27 |
completed | April 10, 2026, 6:57 a.m. |
| NEDg | Description generation | batch_69d8a2b0d8c88190a1a64bd2bbacabbe |
completed | April 10, 2026, 7:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d8a6560ddc81909d540f78a9413b3e |
completed | April 10, 2026, 7:27 a.m. |
Created at: April 6, 2026, 12:07 p.m.