Triple
T18858478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porto Real |
E461240
|
entity |
| Predicate | roadAccess |
P385
|
FINISHED |
| Object |
BR-393
BR-393 is a federal highway in Brazil that connects several municipalities in the state of Rio de Janeiro, serving as an important regional transport corridor.
|
E1347448
|
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: BR-393 | Statement: [Porto Real, roadAccess, BR-393]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BR-393 Context triple: [Porto Real, roadAccess, BR-393]
-
A.
BR-304
BR-304 is a major federal highway in northeastern Brazil that connects key cities in Rio Grande do Norte and Ceará, including Mossoró, and serves as an important regional transport corridor.
-
B.
BR-43
BR-43 is the vehicle registration code assigned to the Madhepura district in the Indian state of Bihar.
-
C.
BR-277
BR-277 is a major Brazilian federal highway in Paraná state that links the inland region to the western border city of Foz do Iguaçu and the Iguaçu Falls area.
-
D.
BR-27
BR-27 is the vehicle registration code assigned to the Nawada district in the Indian state of Bihar.
-
E.
BR-040
BR-040 is a major Brazilian federal highway that connects key cities including Rio de Janeiro, Juiz de Fora, Belo Horizonte, and Brasília.
- 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: BR-393 Triple: [Porto Real, roadAccess, BR-393]
Generated description
BR-393 is a federal highway in Brazil that connects several municipalities in the state of Rio de Janeiro, serving as an important regional transport corridor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BR-393 Target entity description: BR-393 is a federal highway in Brazil that connects several municipalities in the state of Rio de Janeiro, serving as an important regional transport corridor.
-
A.
BR-304
BR-304 is a major federal highway in northeastern Brazil that connects key cities in Rio Grande do Norte and Ceará, including Mossoró, and serves as an important regional transport corridor.
-
B.
BR-43
BR-43 is the vehicle registration code assigned to the Madhepura district in the Indian state of Bihar.
-
C.
BR-277
BR-277 is a major Brazilian federal highway in Paraná state that links the inland region to the western border city of Foz do Iguaçu and the Iguaçu Falls area.
-
D.
BR-27
BR-27 is the vehicle registration code assigned to the Nawada district in the Indian state of Bihar.
-
E.
BR-040
BR-040 is a major Brazilian federal highway that connects key cities including Rio de Janeiro, Juiz de Fora, Belo Horizonte, and Brasília.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c05eaee881909da704cf1374158c |
completed | April 20, 2026, 5:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0575b379688190b0c5e5aa1b2aec71 |
completed | May 14, 2026, 7:11 a.m. |
| NEDg | Description generation | batch_6a05797fe9bc8190af12fce29e461678 |
completed | May 14, 2026, 7:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a057a70e88881909981011f67dfdd32 |
completed | May 14, 2026, 7:32 a.m. |
Created at: April 10, 2026, 11:57 a.m.