Triple

T5107368
Position Surface form Disambiguated ID Type / Status
Subject Malta Lake E115130 entity
Predicate waterSource P4102 FINISHED
Object Cybina River E644942 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: Cybina River | Statement: [Malta Lake, waterSource, Cybina River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cybina River
Context triple: [Malta Lake, waterSource, Cybina River]
  • A. Cybina River chosen
    The Cybina River is a small river in western Poland that flows through the city of Poznań and feeds several local lakes and wetlands.
  • B. Kasplya River
    The Kasplya River is a tributary waterway in Eastern Europe that feeds into the larger Daugava River system.
  • C. Kvichak River
    The Kvichak River is a major river in southwestern Alaska that connects Lake Iliamna to Bristol Bay and supports significant salmon runs and local fishing communities.
  • D. Sakmara River
    The Sakmara River is a major river in Russia that flows through the southern Ural region before joining the Ural River.
  • E. Ozerna River
    The Ozerna River is a smaller watercourse in Russia that serves as one of the tributaries feeding into the Ruza River within the Moscow region’s river system.
  • 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd75a8ee7881908876859402911e5a completed March 20, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b89011a88190b498264ff99e7984 completed March 28, 2026, 11:16 a.m.
Created at: March 20, 2026, 1:41 p.m.