Triple
T18275512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BK Häcken |
E437723
|
entity |
| Predicate | womenTeamOrigin |
P131138
|
FINISHED |
| Object | former Kopparbergs/Göteborg FC |
—
|
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: former Kopparbergs/Göteborg FC | Statement: [BK Häcken, womenTeamOrigin, former Kopparbergs/Göteborg FC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenTeamOrigin Context triple: [BK Häcken, womenTeamOrigin, former Kopparbergs/Göteborg FC]
-
A.
womenTeam
Indicates that the team is composed of women or is designated as a women’s team.
-
B.
womenTeamsCount
Indicates the number of teams composed of women associated with a given entity or context.
-
C.
nationalTeamFor
Indicates that one entity serves as the national team representing another entity, typically a country or nation, in a given sport or activity.
-
D.
countryOfTeam
Indicates that a team is associated with or represents a particular country.
-
E.
nationalTeamType
Indicates the specific category or level of a national team (e.g., senior, youth, futsal) with which an entity is associated.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50051bccc8190832eacdb6945d6b7 |
completed | April 19, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:34 a.m.