Triple
T16019919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henrik Zetterberg |
E388572
|
entity |
| Predicate | playedFor |
P2170
|
FINISHED |
| Object | Timrå IK |
E628614
|
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: Timrå IK | Statement: [Henrik Zetterberg, playedFor, Timrå IK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timrå IK Context triple: [Henrik Zetterberg, playedFor, Timrå IK]
-
A.
Timrå IK
chosen
Timrå IK is a professional ice hockey club from Timrå, Sweden, best known for competing in the country’s top leagues and developing numerous elite players.
-
B.
Råå IF
Råå IF is a Swedish sports club based in the Helsingborg area, best known for its football team and long local tradition.
-
C.
IFK Östersund
IFK Östersund is a Swedish football club from Östersund, known locally for its traditional status and rivalry with Östersunds FK.
-
D.
IFK Umeå
IFK Umeå is a Swedish multi-sport club based in the city of Umeå, known for organizing and competing in various athletic disciplines.
-
E.
Örgryte IS
Örgryte IS is a Swedish sports club best known for its historic football team, one of the oldest in Sweden, based in Gothenburg.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183222e4c81909a3ab51446b671bd |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf2c6128819091d8f3710578834e |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:55 a.m.