Triple

T6840883
Position Surface form Disambiguated ID Type / Status
Subject Niemen E157569 entity
Predicate hasName P744 FINISHED
Object Neman E28957 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: Neman | Statement: [Niemen, hasName, Neman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neman
Context triple: [Niemen, hasName, Neman]
  • A. Neman River chosen
    The Neman River is a major river in Eastern Europe that flows through Belarus and Lithuania before emptying into the Baltic Sea.
  • B. Bóbr River
    The Bóbr River is a major river in southwestern Poland that flows through the Sudetes and Lower Silesia before joining the Oder.
  • C. Vilnia River
    The Vilnia River is a picturesque tributary of the Neris River in Lithuania, flowing through and giving its name to the capital city of Vilnius.
  • D. Narew River
    The Narew River is a major river in northeastern Poland and western Belarus, known for its unique anastomosing channels and as an important waterway feeding into the Vistula River system.
  • E. Biała River
    The Biała River is a tributary of the Dunajec in southern Poland that flows through the city of Tarnów and the Lesser Poland region.
  • 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_69c6882c53608190b99aebef079b23bd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d6b4a1f88190b4f532828697fbd8 completed March 27, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa5cf190819093f3dc9513361e49 completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 2:19 p.m.