Triple
T22138933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joanna Lohman |
E547105
|
entity |
| Predicate | memberOfSportsTeam |
P330
|
FINISHED |
| Object |
Bälinge IF
Bälinge IF is a Swedish sports club best known for its women's football team, which has competed in the country's top division.
|
E1521175
|
NE FINISHED |
How this triple was built (4 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: Bälinge IF | Statement: [Joanna Lohman, memberOfSportsTeam, Bälinge IF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bälinge IF Context triple: [Joanna Lohman, memberOfSportsTeam, Bälinge IF]
-
A.
Sandvikens IF
Sandvikens IF is a Swedish sports club best known for its football team, which has a long tradition and regional significance in Sandviken.
-
B.
Silkeborg IF
Silkeborg IF is a Danish professional football club based in Silkeborg that competes in the country's top leagues and is known for developing domestic talent.
-
C.
Fässbergs IF
Fässbergs IF is a Swedish football club based in Mölndal, known for its long local sporting tradition.
-
D.
Norrby IF
Norrby IF is a Swedish football club based in Borås, known for competing in the national league system and representing one of the city's traditional sports communities.
-
E.
Lidingö SK
Lidingö SK is a Swedish multi-sport club based in Lidingö, known especially for its athletics and orienteering activities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bälinge IF Triple: [Joanna Lohman, memberOfSportsTeam, Bälinge IF]
Generated description
Bälinge IF is a Swedish sports club best known for its women's football team, which has competed in the country's top division.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bälinge IF Target entity description: Bälinge IF is a Swedish sports club best known for its women's football team, which has competed in the country's top division.
-
A.
Sandvikens IF
Sandvikens IF is a Swedish sports club best known for its football team, which has a long tradition and regional significance in Sandviken.
-
B.
Silkeborg IF
Silkeborg IF is a Danish professional football club based in Silkeborg that competes in the country's top leagues and is known for developing domestic talent.
-
C.
Fässbergs IF
Fässbergs IF is a Swedish football club based in Mölndal, known for its long local sporting tradition.
-
D.
Norrby IF
Norrby IF is a Swedish football club based in Borås, known for competing in the national league system and representing one of the city's traditional sports communities.
-
E.
Lidingö SK
Lidingö SK is a Swedish multi-sport club based in Lidingö, known especially for its athletics and orienteering activities.
- F. None of above. chosen
Provenance (5 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_69e11e3a95d88190a3bd80d9471976c3 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129bc7ae881909798c64a4c19adad |
completed | April 28, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a96f864208190911b130fae80a5dc |
completed | May 18, 2026, 4:35 a.m. |
| NEDg | Description generation | batch_6a0a97ae36248190b1f298e1a53cc08f |
completed | May 18, 2026, 4:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a986ea4308190841bf3492a108192 |
completed | May 18, 2026, 4:41 a.m. |
Created at: April 16, 2026, 8:32 p.m.