Triple

T3712442
Position Surface form Disambiguated ID Type / Status
Subject Rhin E81445 entity
Predicate hasTributary P415 FINISHED
Object Moselle E66813 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: Moselle | Statement: [Rhin, hasTributary, Moselle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moselle
Context triple: [Rhin, hasTributary, Moselle]
  • A. Moselle
    Moselle is a department in northeastern France, bordering Germany and Luxembourg, known for its strategic location, industrial history, and mixed French-German cultural heritage.
  • B. Moselle River chosen
    The Moselle River is a major European waterway flowing through France, Luxembourg, and Germany, renowned for its scenic valleys and wine-producing regions.
  • C. Saar River
    The Saar River is a major river in northeastern France and western Germany that flows through the industrial region of Saarland before joining the Moselle.
  • D. Rhens
    Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
  • E. Meuse
    The Meuse is a major European river flowing through France, Belgium, and the Netherlands, historically important for transport, trade, and the development of surrounding regions.
  • 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_69ad8b1a81588190b3f27a5483bb610e completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc9cbc5648190936f93868086167e completed March 8, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5120d23f481908f71e291c089505c completed March 14, 2026, 7:45 a.m.
Created at: March 8, 2026, 3:33 p.m.