Triple
T3101754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilya Kovalchuk |
E64734
|
entity |
| Predicate | memberOfSportsTeam |
P330
|
FINISHED |
| Object | Ak Bars Kazan |
E156583
|
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: Ak Bars Kazan | Statement: [Ilya Kovalchuk, memberOfSportsTeam, Ak Bars Kazan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ak Bars Kazan Context triple: [Ilya Kovalchuk, memberOfSportsTeam, Ak Bars Kazan]
-
A.
Ak Bars Kazan
chosen
Ak Bars Kazan is a professional ice hockey club from Kazan, Russia, renowned as one of the country’s most successful and decorated teams.
-
B.
Buynaksk
Buynaksk is a significant urban center in the Republic of Dagestan in southern Russia, known for its strategic location in the North Caucasus region.
-
C.
Kazan
Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
-
D.
Alma-Atinskaya
Alma-Atinskaya is a southern terminus station of the Moscow Metro, serving as one endpoint of the Zamoskvoretskaya Line.
-
E.
Yoshkar-Ola
Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El Republic.
- 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_69ada26c76ec81908d11f82be573c518 |
completed | March 8, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b203809fac81908047b1139b13cb04 |
completed | March 12, 2026, 12:06 a.m. |
Created at: March 8, 2026, 3:03 p.m.