Triple

T2888810
Position Surface form Disambiguated ID Type / Status
Subject Dila E59569 entity
Predicate formerName P65 FINISHED
Object Dinamo Gori E7244 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: Dinamo Gori | Statement: [Dila, formerName, Dinamo Gori]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dinamo Gori
Context triple: [Dila, formerName, Dinamo Gori]
  • A. Dinamo
    Dinamo is a Moscow Metro station named after the nearby Dynamo sports complex and stadium, serving passengers on the Zamoskvoretskaya Line.
  • B. Dinamo Riga
    Dinamo Riga is a professional ice hockey club based in Riga, Latvia, known for competing in top European and international leagues.
  • C. Dynamo Tbilisi
    Dynamo Tbilisi is a prominent Georgian professional football club based in Tbilisi, historically one of the leading teams in the Caucasus region and a former Soviet Top League and European Cup Winners' Cup champion.
  • D. FC Dila Gori chosen
    FC Dila Gori is a professional Georgian football club based in the city of Gori that competes in the country’s top leagues and domestic competitions.
  • E. Dynamo Moscow
    Dynamo Moscow is a prominent Russian professional ice hockey club based in Moscow, historically known for developing elite players such as Alex Ovechkin.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe04918908190aad08defd1b26d97 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b055f88608819087f258286b2e9e66 completed March 10, 2026, 5:33 p.m.
Created at: March 6, 2026, 10:04 p.m.