Triple
T13801060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SM-sarja |
E331639
|
entity |
| Predicate | notableClub |
P8182
|
FINISHED |
| Object | HIFK |
E66015
|
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: HIFK | Statement: [SM-sarja, notableClub, HIFK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HIFK Context triple: [SM-sarja, notableClub, HIFK]
-
A.
HIFK Helsinki
chosen
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.
-
B.
HIFK Fotboll
HIFK Fotboll is a Finnish professional football club based in Helsinki that competes in the country’s top leagues and is part of the multi-sport club HIFK.
-
C.
Ilves
Ilves is a prominent Finnish sports club from Tampere best known for its ice hockey team competing in the country’s top professional league.
-
D.
FC Honka
FC Honka is a Finnish professional football club based in Espoo that competes in the country’s top-tier league.
-
E.
Jokerit
Jokerit is a professional ice hockey club from Helsinki, Finland, known as one of the country’s most successful and popular teams.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ded6c8190851c108ae559a355 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0893a20819081d4001b8dbc9c36 |
completed | May 3, 2026, 8:31 p.m. |
Created at: April 9, 2026, 10:11 p.m.