Triple
T5807381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemish Brabant |
E128778
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Aarschot
Aarschot is a historic city in Belgium known for its medieval architecture, including a prominent Gothic church, and its location along the Demer River.
|
E653742
|
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: Aarschot | Statement: [Flemish Brabant, contains, Aarschot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aarschot Context triple: [Flemish Brabant, contains, Aarschot]
-
A.
Hasselt
Hasselt is a historic small city in the Dutch province of Overijssel, known for its medieval center and canals.
-
B.
Hasselt
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.
Roeselare
Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
-
E.
St. Truiden
St. Truiden is a historic Belgian city in the Limburg region, known for its medieval architecture and fruit-growing countryside.
- 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: Aarschot Triple: [Flemish Brabant, contains, Aarschot]
Generated description
Aarschot is a historic city in Belgium known for its medieval architecture, including a prominent Gothic church, and its location along the Demer River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aarschot Target entity description: Aarschot is a historic city in Belgium known for its medieval architecture, including a prominent Gothic church, and its location along the Demer River.
-
A.
Hasselt
Hasselt is a historic small city in the Dutch province of Overijssel, known for its medieval center and canals.
-
B.
Hasselt
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.
Roeselare
Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
-
E.
St. Truiden
St. Truiden is a historic Belgian city in the Limburg region, known for its medieval architecture and fruit-growing countryside.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b17417081908779741b9bfbb720 |
completed | March 22, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7daed5d188190b499151e636d206d |
completed | March 28, 2026, 1:43 p.m. |
| NEDg | Description generation | batch_69c7dbc1ff0c8190bc7639a74a5d3af3 |
completed | March 28, 2026, 1:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7dc6873a081908ea4e953430ec20b |
completed | March 28, 2026, 1:49 p.m. |
Created at: March 22, 2026, 3:52 p.m.