Triple

T3103548
Position Surface form Disambiguated ID Type / Status
Subject Syvash E64776 entity
Predicate alsoKnownAs P39 FINISHED
Object Sivash E9735 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: Sivash | Statement: [Syvash, alsoKnownAs, Sivash]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sivash
Context triple: [Syvash, alsoKnownAs, Sivash]
  • A. Rybinsk
    Rybinsk is a historic Russian city on the Volga River known for its role as a major river port and grain-shipping center.
  • B. Kaspi
    Kaspi is a town in central Georgia known as an industrial center and regional hub within the Shida Kartli area.
  • C. Dvina Bay
    Dvina Bay is a large inlet of the White Sea in northwestern Russia, known for its connection to the Northern Dvina River and the port city of Arkhangelsk.
  • D. Azov
    Azov is a historic port city in Russia’s Rostov Oblast, located near the mouth of the Don River by the Sea of Azov.
  • E. Sea of Azov chosen
    The Sea of Azov is a shallow inland sea in Eastern Europe connected to the Black Sea, bordered by Ukraine and Russia and known for its strategic and economic importance.
  • 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_69ad857dc98481909e585dc3372e3ed5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada26f376c8190a049399e33314d52 completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b203846a108190a97c30c463e119b1 completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:03 p.m.