Triple

T539637
Position Surface form Disambiguated ID Type / Status
Subject Black Sea E12600 entity
Predicate receivesRiver P4359 FINISHED
Object Dniester E41326 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: Dniester | Statement: [Black Sea, receivesRiver, Dniester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dniester
Context triple: [Black Sea, receivesRiver, Dniester]
  • A. Dniester chosen
    The Dniester is a major river in Eastern Europe that flows through Ukraine and Moldova before emptying into the Black Sea.
  • B. Dnieper
    The Dnieper is a major Eastern European river that flows through Russia, Belarus, and Ukraine before emptying into the Black Sea.
  • C. Prut River
    The Prut River is a significant Eastern European waterway that flows through Ukraine, Moldova, and Romania, forming much of the border between Romania and Moldova before joining the Danube.
  • D. Maritsa
    Maritsa is a significant river in the Balkans that flows through Bulgaria, Greece, and Turkey before emptying into the Aegean Sea.
  • E. Danube
    The Danube is one of Europe's longest and most historically significant rivers, flowing from Germany to the Black Sea and passing through numerous Central and Eastern European countries.
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a496dd31c88190b3114805aa31931c completed March 1, 2026, 7:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e9b6d1088190a925b1b3d78e9674 completed March 2, 2026, 1:36 a.m.
Created at: March 1, 2026, 7:32 p.m.