Triple
T14159963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jette |
E350909
|
entity |
| Predicate | hasHealthcareFacility |
P12416
|
FINISHED |
| Object |
UZ Brussel
UZ Brussel is a major university hospital in Brussels, Belgium, known for providing comprehensive medical care, research, and teaching services.
|
E1084162
|
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: UZ Brussel | Statement: [Jette, hasHealthcareFacility, UZ Brussel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UZ Brussel Context triple: [Jette, hasHealthcareFacility, UZ Brussel]
-
A.
Zulte
Zulte is a municipality in the Belgian province of East Flanders.
-
B.
Waasland-Beveren
Waasland-Beveren is a Belgian professional football club based in Beveren, known for competing in the country’s football league system.
-
C.
Club Brugge KV
Club Brugge KV is one of Belgium’s most successful and popular football clubs, known for its multiple league titles and regular participation in European competitions.
-
D.
Royal Antwerp F.C.
Royal Antwerp F.C. is a historic Belgian professional football club based in Antwerp and one of the oldest clubs in the country.
-
E.
Cercle Brugge KSV
Cercle Brugge KSV is a Belgian professional football club from Bruges, known for its historic presence in the top tiers of Belgian football and its local and national rivalries.
- 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: UZ Brussel Triple: [Jette, hasHealthcareFacility, UZ Brussel]
Generated description
UZ Brussel is a major university hospital in Brussels, Belgium, known for providing comprehensive medical care, research, and teaching services.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UZ Brussel Target entity description: UZ Brussel is a major university hospital in Brussels, Belgium, known for providing comprehensive medical care, research, and teaching services.
-
A.
Zulte
Zulte is a municipality in the Belgian province of East Flanders.
-
B.
Waasland-Beveren
Waasland-Beveren is a Belgian professional football club based in Beveren, known for competing in the country’s football league system.
-
C.
Club Brugge KV
Club Brugge KV is one of Belgium’s most successful and popular football clubs, known for its multiple league titles and regular participation in European competitions.
-
D.
Royal Antwerp F.C.
Royal Antwerp F.C. is a historic Belgian professional football club based in Antwerp and one of the oldest clubs in the country.
-
E.
Cercle Brugge KSV
Cercle Brugge KSV is a Belgian professional football club from Bruges, known for its historic presence in the top tiers of Belgian football and its local and national rivalries.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61393f308190bb357e2bd1916f94 |
completed | April 14, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7f166988190a96d01fb4bd1438e |
completed | May 7, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_69fd05f31d9c81908b12befa499fae08 |
completed | May 7, 2026, 9:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd068196fc8190b0c5620c754d2a5c |
completed | May 7, 2026, 9:39 p.m. |
Created at: April 10, 2026, 12:59 a.m.