Triple
T8098542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Nivelles |
E189046
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Tubize |
E662535
|
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: Tubize | Statement: [Arrondissement of Nivelles, containsMunicipality, Tubize]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tubize Context triple: [Arrondissement of Nivelles, containsMunicipality, Tubize]
-
A.
Tubize
chosen
Tubize is a municipality in Walloon Brabant, Belgium, known for its industrial heritage and location along the Brussels–Charleroi Canal.
-
B.
Braine-l'Alleud
Braine-l'Alleud is a municipality in Walloon Brabant, Belgium, known for encompassing much of the historic Waterloo battlefield.
-
C.
Mont-Saint-Guibert
Mont-Saint-Guibert is a municipality in the province of Walloon Brabant in the French-speaking Walloon region of Belgium.
-
D.
Binche
Binche is a historic town in the Walloon region of Belgium, renowned for its well-preserved medieval architecture and its UNESCO-recognized Carnival of Binche.
-
E.
Gosselies
Gosselies is a district of the city of Charleroi in Wallonia, Belgium, known for its proximity to Brussels South Charleroi Airport and its industrial and aeronautical activities.
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42961ad4819085d023427fc5ac5f |
completed | March 31, 2026, 3:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4d5b80b48190909ca7775fda2ed9 |
completed | April 2, 2026, 11:04 a.m. |
Created at: March 30, 2026, 5:30 p.m.