Triple
T7092708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasselt |
E165235
|
entity |
| Predicate | hasSportsTeam |
P330
|
FINISHED |
| Object |
KRC Hasselt
KRC Hasselt is a Belgian football club based in the city of Hasselt.
|
E642686
|
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: KRC Hasselt | Statement: [Hasselt, hasSportsTeam, KRC Hasselt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KRC Hasselt Context triple: [Hasselt, hasSportsTeam, KRC Hasselt]
-
A.
KRC Genk
KRC Genk is a Belgian professional football club known for developing top talents, including Kevin De Bruyne, and competing in the country’s top division.
-
B.
KV Mechelen
KV Mechelen is a Belgian professional football club known for competing in the country’s top leagues and for its passionate local fan base.
-
C.
Oud-Heverlee Leuven
Oud-Heverlee Leuven is a Belgian professional football club based in the city of Leuven that competes in the country’s top leagues.
-
D.
KAA Gent
KAA Gent is a Belgian professional football club based in Ghent, known for competing in the country’s top division and developing notable players such as Kevin De Bruyne.
-
E.
K.S.C. Lokeren Oost-Vlaanderen
K.S.C. Lokeren Oost-Vlaanderen was a Belgian professional football club based in Lokeren, known for competing in the country’s top division and featuring several notable international players.
- 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: KRC Hasselt Triple: [Hasselt, hasSportsTeam, KRC Hasselt]
Generated description
KRC Hasselt is a Belgian football club based in the city of Hasselt.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KRC Hasselt Target entity description: KRC Hasselt is a Belgian football club based in the city of Hasselt.
-
A.
KRC Genk
KRC Genk is a Belgian professional football club known for developing top talents, including Kevin De Bruyne, and competing in the country’s top division.
-
B.
KV Mechelen
KV Mechelen is a Belgian professional football club known for competing in the country’s top leagues and for its passionate local fan base.
-
C.
Oud-Heverlee Leuven
Oud-Heverlee Leuven is a Belgian professional football club based in the city of Leuven that competes in the country’s top leagues.
-
D.
KAA Gent
KAA Gent is a Belgian professional football club based in Ghent, known for competing in the country’s top division and developing notable players such as Kevin De Bruyne.
-
E.
K.S.C. Lokeren Oost-Vlaanderen
K.S.C. Lokeren Oost-Vlaanderen was a Belgian professional football club based in Lokeren, known for competing in the country’s top division and featuring several notable international players.
- 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_69c79c960484819098228cebccb8c935 |
completed | March 28, 2026, 9:17 a.m. |
| NEDg | Description generation | batch_69c79ef0e8448190a8f0a7572ee87f5f |
completed | March 28, 2026, 9:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79fa4e69881909cf991a5d0ab3de9 |
completed | March 28, 2026, 9:30 a.m. |
Created at: March 27, 2026, 2:41 p.m.