Triple
T2355381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oleg Znarok |
E47540
|
entity |
| Predicate | memberOfSportsTeam |
P330
|
FINISHED |
| Object | Dinamo Riga |
E114622
|
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 Riga | Statement: [Oleg Znarok, memberOfSportsTeam, Dinamo Riga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dinamo Riga Context triple: [Oleg Znarok, memberOfSportsTeam, Dinamo Riga]
-
A.
Dinamo Riga
chosen
Dinamo Riga is a professional ice hockey club based in Riga, Latvia, known for competing in top European and international leagues.
-
B.
Dinamo
Dinamo is a Moscow Metro station named after the nearby Dynamo sports complex and stadium, serving passengers on the Zamoskvoretskaya Line.
-
C.
Riga FC
Riga FC is a professional football club based in Riga, Latvia, competing in the Latvian Higher League.
-
D.
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.
-
E.
Lokomotiv Moscow
Lokomotiv Moscow is a major Russian professional football club from Moscow, known for competing in the Russian Premier League and being one of the city’s traditional powerhouses.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc6fd4e488190b763a1c9b5d18f2c |
completed | March 7, 2026, 6:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea888b5a881909b1f91562957388d |
completed | March 9, 2026, 11:01 a.m. |
Created at: March 4, 2026, 7:54 p.m.