Triple

T4273704
Position Surface form Disambiguated ID Type / Status
Subject Mỹ Tho E96995 entity
Predicate hasTransport P1298 FINISHED
Object National Route 1A E248401 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: National Route 1A | Statement: [Mỹ Tho, hasTransport, National Route 1A]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: National Route 1A
Context triple: [Mỹ Tho, hasTransport, National Route 1A]
  • A. National Route 1A chosen
    National Route 1A is Vietnam’s primary north–south highway, running the length of the country and connecting major cities, provinces, and economic regions.
  • B. National Route 1
    National Route 1 is a major Japanese highway that links Tokyo with Osaka, passing through key urban and industrial areas along the Pacific coast of Honshu.
  • C. National Route 17
    National Route 17 is a major South Korean highway that runs north–south across the country, connecting multiple cities and regions including Eumseong County.
  • D. National Route 136
    National Route 136 is a major Japanese highway on the Izu Peninsula in Shizuoka Prefecture, connecting coastal and inland cities including Mishima.
  • E. National Route 3
    National Route 3 is a major South Korean highway that runs north–south, connecting multiple regions and cities across the country.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501abb74819086b2f04ac7a5c114 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7ace6c881908e1fbde95a2a3c04 completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:07 p.m.