Triple
T7092709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasselt |
E165235
|
entity |
| Predicate | hasSportsVenue |
P587
|
FINISHED |
| Object |
Alverbergstadion
Alverbergstadion is a football stadium located in Hasselt, Belgium, serving as a home ground for local football clubs and sporting events.
|
E643739
|
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: Alverbergstadion | Statement: [Hasselt, hasSportsVenue, Alverbergstadion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alverbergstadion Context triple: [Hasselt, hasSportsVenue, Alverbergstadion]
-
A.
Lerkendal Stadion
Lerkendal Stadion is a major football stadium in Trondheim, Norway, best known as the home ground of top Norwegian club Rosenborg BK.
-
B.
Vålerenga Stadion
Vålerenga Stadion is a football stadium in Oslo, Norway, serving as the home ground of the Vålerenga Fotball club.
-
C.
Gjøvik Stadium
Gjøvik Stadium is a sports arena in Gjøvik, Norway, primarily used for football and athletics events.
-
D.
Nadderud Stadion
Nadderud Stadion is a football stadium in Bærum, Norway, best known as the long-time home ground of Norwegian club Stabæk Fotball.
-
E.
Åråsen Stadion
Åråsen Stadion is a football stadium in Lillestrøm, Norway, best known as the main home ground of Lillestrøm SK and a prominent venue in Norwegian football.
- 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: Alverbergstadion Triple: [Hasselt, hasSportsVenue, Alverbergstadion]
Generated description
Alverbergstadion is a football stadium located in Hasselt, Belgium, serving as a home ground for local football clubs and sporting events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alverbergstadion Target entity description: Alverbergstadion is a football stadium located in Hasselt, Belgium, serving as a home ground for local football clubs and sporting events.
-
A.
Lerkendal Stadion
Lerkendal Stadion is a major football stadium in Trondheim, Norway, best known as the home ground of top Norwegian club Rosenborg BK.
-
B.
Vålerenga Stadion
Vålerenga Stadion is a football stadium in Oslo, Norway, serving as the home ground of the Vålerenga Fotball club.
-
C.
Gjøvik Stadium
Gjøvik Stadium is a sports arena in Gjøvik, Norway, primarily used for football and athletics events.
-
D.
Nadderud Stadion
Nadderud Stadion is a football stadium in Bærum, Norway, best known as the long-time home ground of Norwegian club Stabæk Fotball.
-
E.
Åråsen Stadion
Åråsen Stadion is a football stadium in Lillestrøm, Norway, best known as the main home ground of Lillestrøm SK and a prominent venue in Norwegian football.
- 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_69c6887e8c10819091cee237560d32da |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e532513c8190968eea8a0d3235a0 |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a31e3fec8190b22da130f7cbaaf9 |
completed | March 28, 2026, 9:45 a.m. |
| NEDg | Description generation | batch_69c7a426cc6c8190b3d3cce1233dd068 |
completed | March 28, 2026, 9:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7a48162e081909e03ed01f305c46f |
completed | March 28, 2026, 9:50 a.m. |
Created at: March 27, 2026, 2:41 p.m.