Triple
T22350157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vágur |
E552505
|
entity |
| Predicate | hasSportsClub |
P346
|
FINISHED |
| Object |
VB Vágur
VB Vágur is a Faroese football club based in the village of Vágur, known for competing in the national football leagues of the Faroe Islands.
|
E1532736
|
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: VB Vágur | Statement: [Vágur, hasSportsClub, VB Vágur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VB Vágur Context triple: [Vágur, hasSportsClub, VB Vágur]
-
A.
Vigel
Vigel is an electronic dance music producer and DJ known for his work in the progressive and psytrance scenes, including collaborations with acts like Vini Vici.
-
B.
Valbo
Valbo is a locality in Gävleborg County, Sweden, known as the hometown of NHL ice hockey star Nicklas Bäckström.
-
C.
Vangteh
Vangteh is a dialect of the Tedim Chin language spoken by a subgroup of the Chin people in Myanmar.
-
D.
Vingrau
Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
-
E.
Vanur
Vanur is a town in the Viluppuram district of the Indian state of Tamil Nadu, known primarily as a local administrative and commercial center for surrounding rural areas.
- 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: VB Vágur Triple: [Vágur, hasSportsClub, VB Vágur]
Generated description
VB Vágur is a Faroese football club based in the village of Vágur, known for competing in the national football leagues of the Faroe Islands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VB Vágur Target entity description: VB Vágur is a Faroese football club based in the village of Vágur, known for competing in the national football leagues of the Faroe Islands.
-
A.
Vigel
Vigel is an electronic dance music producer and DJ known for his work in the progressive and psytrance scenes, including collaborations with acts like Vini Vici.
-
B.
Valbo
Valbo is a locality in Gävleborg County, Sweden, known as the hometown of NHL ice hockey star Nicklas Bäckström.
-
C.
Vangteh
Vangteh is a dialect of the Tedim Chin language spoken by a subgroup of the Chin people in Myanmar.
-
D.
Vingrau
Vingrau is a small commune in southern France’s Pyrénées-Orientales department, known for its wine production and scenic location amid rugged limestone hills.
-
E.
Vanur
Vanur is a town in the Viluppuram district of the Indian state of Tamil Nadu, known primarily as a local administrative and commercial center for surrounding rural areas.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1579ad6708190ba4af97a02d0758d |
completed | April 29, 2026, 12:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae05a25b881908bfdca01c863fc0c |
completed | May 18, 2026, 9:48 a.m. |
| NEDg | Description generation | batch_6a0ae2c1dc888190a32541b120332e88 |
completed | May 18, 2026, 9:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ae3855838819080bf6883946b62f7 |
completed | May 18, 2026, 10:01 a.m. |
Created at: April 16, 2026, 8:43 p.m.