Triple

T7126710
Position Surface form Disambiguated ID Type / Status
Subject Loon Lake E166080 entity
Predicate watercourse P415 FINISHED
Object Rubicon River E194651 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: Rubicon River | Statement: [Loon Lake, watercourse, Rubicon River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rubicon River
Context triple: [Loon Lake, watercourse, Rubicon River]
  • A. Rubicon River chosen
    The Rubicon River is a small river in northern Italy historically famous as the boundary Julius Caesar crossed in 49 BCE, symbolizing a point of no return.
  • B. Segre River
    The Segre River is a significant river in northeastern Spain that flows through the Pyrenees and Catalonia before joining the Ebro River.
  • C. Sym River
    The Sym River is a significant waterway in central Siberia that flows through the Krasnoyarsk Krai region of Russia.
  • D. Paterson River
    The Paterson River is a significant waterway in New South Wales, Australia, flowing through rural landscapes and contributing to the Hunter River catchment.
  • E. Seille River
    The Seille River is a tributary of the Moselle in northeastern France that flows through the city of Metz.
  • 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_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e64ee8ac81909ee1c7cb1db3af33 completed March 27, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a3357e548190bb56c31843c69f95 completed March 28, 2026, 9:45 a.m.
Created at: March 27, 2026, 2:44 p.m.