Triple
T5658828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemish Limburg |
E124685
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Hasselt |
E165235
|
NE FINISHED |
How this triple was built (2 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: Hasselt | Statement: [Flemish Limburg, hasMunicipality, Hasselt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasselt Context triple: [Flemish Limburg, hasMunicipality, Hasselt]
-
A.
Hasselt
Hasselt is a historic small city in the Dutch province of Overijssel, known for its medieval center and canals.
-
B.
Hasselt
chosen
Hasselt is a city in northeastern Belgium that serves as the capital of the province of Limburg in the Flemish region.
-
C.
Vilvoorde
Vilvoorde is a city in the Flemish Region of Belgium, located just north of Brussels and known as part of the capital’s broader metropolitan area.
-
D.
Aalst
Aalst is a historic city in the Belgian province of East Flanders, known for its textile industry and famous annual carnival.
-
E.
Leuven
Leuven is a historic Belgian city known for hosting KU Leuven, one of Europe’s leading research universities, and for its vibrant academic and cultural life.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c0082774a481909d7e63fb2aad56ac |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022fd9b148190bd4aa9c43500949f |
completed | March 22, 2026, 5:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7239e1ea481908c64d8a2d600aa30 |
completed | March 28, 2026, 12:41 a.m. |
Created at: March 22, 2026, 3:42 p.m.