Triple
T5658844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemish Limburg |
E124685
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Lummen
Lummen is a municipality in the Belgian province of Limburg, known for its rural character and location at the junction of several major motorways.
|
E537805
|
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: Lummen | Statement: [Flemish Limburg, hasMunicipality, Lummen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lummen Context triple: [Flemish Limburg, hasMunicipality, Lummen]
-
A.
Edzell
Edzell is a small historic village in Angus, Scotland, known for its picturesque setting, nearby glens, and the ruins of Edzell Castle.
-
B.
Iveland
Iveland is a small rural municipality in southern Norway known for its forests, agriculture, and mineral resources.
-
C.
Sallands
Sallands is a Dutch Low Saxon dialect spoken in the Salland region of the province of Overijssel in the Netherlands.
-
D.
Hodnet
Hodnet is a rural village in Shropshire, England, known for its historic parish church, traditional architecture, and proximity to country estates and parkland.
-
E.
Malhamdale
Malhamdale is a picturesque valley in North Yorkshire, England, renowned for its dramatic limestone scenery, including Malham Cove, Gordale Scar, and Malham Tarn.
- 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: Lummen Triple: [Flemish Limburg, hasMunicipality, Lummen]
Generated description
Lummen is a municipality in the Belgian province of Limburg, known for its rural character and location at the junction of several major motorways.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lummen Target entity description: Lummen is a municipality in the Belgian province of Limburg, known for its rural character and location at the junction of several major motorways.
-
A.
Edzell
Edzell is a small historic village in Angus, Scotland, known for its picturesque setting, nearby glens, and the ruins of Edzell Castle.
-
B.
Iveland
Iveland is a small rural municipality in southern Norway known for its forests, agriculture, and mineral resources.
-
C.
Sallands
Sallands is a Dutch Low Saxon dialect spoken in the Salland region of the province of Overijssel in the Netherlands.
-
D.
Hodnet
Hodnet is a rural village in Shropshire, England, known for its historic parish church, traditional architecture, and proximity to country estates and parkland.
-
E.
Malhamdale
Malhamdale is a picturesque valley in North Yorkshire, England, renowned for its dramatic limestone scenery, including Malham Cove, Gordale Scar, and Malham Tarn.
- 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_69c04da37ffc819095f33e7e66e7c1d0 |
completed | March 22, 2026, 8:14 p.m. |
| NEDg | Description generation | batch_69c04edf30448190a60eda49b8b031a0 |
completed | March 22, 2026, 8:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04fb62690819083327781cb857ccc |
completed | March 22, 2026, 8:23 p.m. |
Created at: March 22, 2026, 3:42 p.m.