Triple
T22150929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonheiden |
E547408
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Haacht |
—
|
NE NERFINISHED |
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: Haacht | Statement: [Bonheiden, hasNeighbouringMunicipality, Haacht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haacht Context triple: [Bonheiden, hasNeighbouringMunicipality, Haacht]
-
A.
Haacht
chosen
Haacht is a municipality in the Flemish Brabant province of Belgium, known for its local brewery and semi-rural character near the city of Leuven.
-
B.
Hachen
Hachen is a district (Ortsteil) of the town of Sundern in the Hochsauerland region of North Rhine-Westphalia, Germany.
-
C.
Hagenborgh
Hagenborgh is a notable landmark building in the Dutch city of Almelo, recognized for its prominent role in the local urban landscape.
-
D.
Harste
Harste is a village and municipal district of Bovenden in Lower Saxony, Germany.
-
E.
Hassela
Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f37dac8190a7cecb12f4271515 |
completed | April 28, 2026, 9:43 p.m. |
Created at: April 16, 2026, 8:33 p.m.