Triple
T19085860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BR-163 highway |
E467146
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | BR-101 highway |
—
|
NE NERFINISHED |
How this triple was built (2 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-101 highway | Statement: [BR-163 highway, connectsTo, BR-101 highway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BR-101 highway Context triple: [BR-163 highway, connectsTo, BR-101 highway]
-
A.
BR-116 highway
BR-116 highway is one of Brazil's longest and most important federal highways, running north–south and connecting major cities across the country.
-
B.
BR-158 highway
BR-158 highway is a major Brazilian federal road that runs north–south through several central and southern states, supporting agricultural transport and regional integration.
-
C.
BR-163 highway
BR-163 highway is a major Brazilian federal road that runs through the Amazon region, linking the interior agricultural areas to key river ports and export routes.
-
D.
BR-110
BR-110 is a federal highway in Brazil that connects the city of Mossoró to other regions in the country’s Northeast.
-
E.
BR-101
chosen
BR-101 is one of Brazil’s longest and most important federal highways, running along much of the country’s Atlantic coast and linking numerous major cities and states.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e346f57c8190a6299e09a0be9e05 |
completed | April 20, 2026, 8:26 a.m. |
Created at: April 10, 2026, 12:04 p.m.