Triple

T8385829
Position Surface form Disambiguated ID Type / Status
Subject Sequani E197816 entity
Predicate capital P234 FINISHED
Object Vesontio E725492 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: Vesontio | Statement: [Sequani, capital, Vesontio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vesontio
Context triple: [Sequani, capital, Vesontio]
  • A. Vesontio chosen
    Vesontio was the ancient Roman city that later became Besançon, an important urban and military center in the province of Germania Superior.
  • B. Vehmaa
    Vehmaa is a small rural municipality in southwestern Finland known for its granite quarries and traditional countryside landscape.
  • C. Viimsi
    Viimsi is a rapidly developing suburban municipality in northern Estonia, located just northeast of the capital city Tallinn.
  • D. Summajärvi
    Summajärvi is a lake on the Karelian Isthmus in present-day Russia, historically associated with the nearby village of Summa and the Winter War battles fought in the area.
  • E. Vihti
    Vihti is a municipality in southern Finland located within the Uusimaa region, known for its lakes, rural landscapes, and proximity to the Helsinki metropolitan area.
  • 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_69ca82f749388190bffbea6dfb509016 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80e1bcdc81909111aa33ee996e0a completed March 31, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde8312be48190bd5896adc8bb4e95 completed April 2, 2026, 3:53 a.m.
Created at: March 30, 2026, 6:02 p.m.