Triple
T5658843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemish Limburg |
E124685
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Tessenderlo
Tessenderlo is a municipality in the Belgian province of Limburg, known for its chemical industry and location near the Albert Canal.
|
E635972
|
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: Tessenderlo | Statement: [Flemish Limburg, hasMunicipality, Tessenderlo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessenderlo Context triple: [Flemish Limburg, hasMunicipality, Tessenderlo]
-
A.
Roeselare
Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
-
B.
Oudenarde
Oudenarde (Oudenaarde) is a historic town in East Flanders, Belgium, known for its medieval architecture, tapestry production, and role in early modern European conflicts.
-
C.
Merelbeke
Merelbeke is a municipality in East Flanders, Belgium, known in part for hosting Ghent University's Faculty of Veterinary Medicine.
-
D.
Beringen
Beringen is a city and municipality in the Belgian province of Limburg, known for its coal mining heritage and the be-MINE industrial heritage site.
-
E.
Aalst
Aalst is a historic city in the Belgian province of East Flanders, known for its textile industry and famous annual carnival.
- 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: Tessenderlo Triple: [Flemish Limburg, hasMunicipality, Tessenderlo]
Generated description
Tessenderlo is a municipality in the Belgian province of Limburg, known for its chemical industry and location near the Albert Canal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tessenderlo Target entity description: Tessenderlo is a municipality in the Belgian province of Limburg, known for its chemical industry and location near the Albert Canal.
-
A.
Roeselare
Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
-
B.
Oudenarde
Oudenarde (Oudenaarde) is a historic town in East Flanders, Belgium, known for its medieval architecture, tapestry production, and role in early modern European conflicts.
-
C.
Merelbeke
Merelbeke is a municipality in East Flanders, Belgium, known in part for hosting Ghent University's Faculty of Veterinary Medicine.
-
D.
Beringen
Beringen is a city and municipality in the Belgian province of Limburg, known for its coal mining heritage and the be-MINE industrial heritage site.
-
E.
Aalst
Aalst is a historic city in the Belgian province of East Flanders, known for its textile industry and famous annual carnival.
- 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_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_69c769cd39e081908624c8471b9131a1 |
completed | March 28, 2026, 5:40 a.m. |
| NEDg | Description generation | batch_69c76da6e9e4819097c42d5a74efb3e7 |
completed | March 28, 2026, 5:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76e01a3fc8190b766188a0c243385 |
completed | March 28, 2026, 5:58 a.m. |
Created at: March 22, 2026, 3:42 p.m.