Triple

T10029207
Position Surface form Disambiguated ID Type / Status
Subject Rio–Niterói Bridge E204809 entity
Predicate partOf P40 FINISHED
Object BR-101 E582242 NE FINISHED

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 | Statement: [Rio–Niterói Bridge, partOf, BR-101]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BR-101
Context triple: [Rio–Niterói Bridge, partOf, BR-101]
  • A. 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.
  • B. BR-10
    BR-10 is the vehicle registration code assigned to the Bhagalpur district in the Indian state of Bihar.
  • C. BR-110
    BR-110 is a federal highway in Brazil that connects the city of Mossoró to other regions in the country’s Northeast.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca834d77188190ad645e33e8ca3200 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcde69bd08190a5c79ec8487dfff6 completed April 2, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69d282351ebc8190b22bf3964823b0ee completed April 5, 2026, 3:39 p.m.
Created at: March 30, 2026, 8:54 p.m.