Triple

T4016294
Position Surface form Disambiguated ID Type / Status
Subject Vesle River E90768 entity
Predicate hasNameInFrench P6538 FINISHED
Object Vesle E90768 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: Vesle | Statement: [Vesle River, hasNameInFrench, Vesle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vesle
Context triple: [Vesle River, hasNameInFrench, Vesle]
  • A. Veavågen
    Veavågen is a coastal village in Karmøy municipality in Rogaland county, Norway, known for its fishing industry and maritime character.
  • B. Vesdre
    The Vesdre is a river in eastern Belgium that flows through the Ardennes and Liège region before joining the Meuse.
  • C. Børselva
    Børselva is a river in northern Norway known for flowing into Porsangerfjorden and for its scenic Arctic landscape and salmon fishing.
  • D. Vesle River chosen
    The Vesle River is a waterway in northeastern France that flows through the city of Reims and is a tributary of the Aisne River.
  • E. Moldeelva
    Moldeelva is a river flowing through the Norwegian town of Molde, contributing to its landscape and local environment.
  • 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_69aed95e44088190aff7d90a151b1b20 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaa7352481908232534c89a698e7 completed March 9, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c768e5481908b184332e3c73588 completed March 14, 2026, 11:54 a.m.
Created at: March 9, 2026, 3:35 p.m.