Triple
T31855626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umeå IK (women) |
E813187
|
entity |
| Predicate | DamallsvenskanTitlesSeason |
P172669
|
FINISHED |
| Object | 2000 |
—
|
LITERAL 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: 2000 | Statement: [Umeå IK (women), DamallsvenskanTitlesSeason, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DamallsvenskanTitlesSeason Context triple: [Umeå IK (women), DamallsvenskanTitlesSeason, 2000]
-
A.
bestUefaWomen’sChampionshipResult
Indicates the highest level of success an entity has achieved in the UEFA Women's Championship competition.
-
B.
FIFAWomen'sWorldCupAllTimeTopScorer
Indicates that the subject holds the record for scoring the most goals in the history of the FIFA Women's World Cup.
-
C.
RussianSuperleagueTitles
Indicates the number of Russian Superleague championship titles an entity has won.
-
D.
goalsBySweden
Indicates the number of goals that were scored by Sweden in a given match or context.
-
E.
euroHockeyTourTitles
Indicates the number of Euro Hockey Tour championship titles an entity has won.
- F. None of above. chosen
Provenance (4 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_69f348ebf32881908d9439646933dc76 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b069d4748190b401e518e0a53e4f |
completed | May 3, 2026, 2:18 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6af7d92008190aead47eaae8cc091 |
completed | May 3, 2026, 2:14 a.m. |
Created at: April 30, 2026, 11:52 p.m.