Triple

T14938410
Position Surface form Disambiguated ID Type / Status
Subject Colmar-Berg E372457 entity
Predicate traversedBy P225 FINISHED
Object Alzette River E327035 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: Alzette River | Statement: [Colmar-Berg, traversedBy, Alzette River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alzette River
Context triple: [Colmar-Berg, traversedBy, Alzette River]
  • A. Alzette River chosen
    The Alzette River is a major river in Luxembourg and northeastern France that flows through key cities including Luxembourg City and Esch-sur-Alzette before joining the Sauer.
  • B. Neris River
    The Neris River is a major river in Belarus and Lithuania that flows through the city of Kaunas before joining the Nemunas River.
  • C. Deûle River
    The Deûle River is a canalised river in northern France that flows through the city of Lille and serves as an important waterway in the region.
  • D. Orge River
    The Orge River is a tributary of the Seine in northern France that flows through several towns in the Île-de-France region.
  • E. Akmena-Danė River
    The Akmena-Danė River is a waterway in western Lithuania that flows through the port city of Klaipėda before emptying into the Curonian Lagoon.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded64904d88190b6b4140da8e8199d completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e8e9c0c81909cfb1e02987527c0 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 2:38 a.m.