Triple
T3263182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teemu Selänne |
E68459
|
entity |
| Predicate | playedFor |
P2170
|
FINISHED |
| Object | Jokerit |
E66429
|
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: Jokerit | Statement: [Teemu Selänne, playedFor, Jokerit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jokerit Context triple: [Teemu Selänne, playedFor, Jokerit]
-
A.
Jokerit
chosen
Jokerit is a professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and popular teams.
-
B.
HIFK Helsinki
HIFK Helsinki is a prominent professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and traditional teams in the Liiga.
-
C.
Kärpät Oulu
Kärpät Oulu is a prominent Finnish professional ice hockey club from Oulu, known as one of the most successful teams in the Liiga.
-
D.
FC Honka
FC Honka is a Finnish professional football club based in Espoo that competes in the country’s top-tier league.
-
E.
Brynas IF
Brynäs IF is a professional Swedish ice hockey club based in Gävle, historically one of the country's most successful teams and a notable developer of NHL talent.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafaa35e48190b894ca41dd65932b |
completed | March 8, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bb1c468819083b50b5858f8afe0 |
completed | March 12, 2026, 11:26 p.m. |
Created at: March 8, 2026, 3:09 p.m.