Triple
T16989772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chamber of Representatives of Belgium |
E412160
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
Kamer
Kamer is the Dutch term commonly used to refer to the Belgian Chamber of Representatives, the lower house of the country's federal parliament.
|
E1244391
|
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: Kamer | Statement: [Chamber of Representatives of Belgium, abbreviation, Kamer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamer Context triple: [Chamber of Representatives of Belgium, abbreviation, Kamer]
-
A.
Cámara
Cámara is an Argentine Navy officer known for his service in Argentina's naval forces.
-
B.
Kamer Daron
Kamer Daron is the given first name of Daron Acemoglu, a prominent Turkish-American economist known for his work on political economy and institutional development.
-
C.
Hooghkamer
Hooghkamer is a residential neighborhood in the Dutch town of Leiderdorp, located in the province of South Holland.
-
D.
Kamberi
Kamberi are an ethnic group in northwestern Nigeria, primarily inhabiting rural areas of Kebbi State and known for their distinct language and traditional cultural practices.
-
E.
Camira
Camira is a residential suburb located within the Ipswich City Council area in South East Queensland, Australia.
- 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: Kamer Triple: [Chamber of Representatives of Belgium, abbreviation, Kamer]
Generated description
Kamer is the Dutch term commonly used to refer to the Belgian Chamber of Representatives, the lower house of the country's federal parliament.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kamer Target entity description: Kamer is the Dutch term commonly used to refer to the Belgian Chamber of Representatives, the lower house of the country's federal parliament.
-
A.
Cámara
Cámara is an Argentine Navy officer known for his service in Argentina's naval forces.
-
B.
Kamer Daron
Kamer Daron is the given first name of Daron Acemoglu, a prominent Turkish-American economist known for his work on political economy and institutional development.
-
C.
Hooghkamer
Hooghkamer is a residential neighborhood in the Dutch town of Leiderdorp, located in the province of South Holland.
-
D.
Kamberi
Kamberi are an ethnic group in northwestern Nigeria, primarily inhabiting rural areas of Kebbi State and known for their distinct language and traditional cultural practices.
-
E.
Camira
Camira is a residential suburb located within the Ipswich City Council area in South East Queensland, Australia.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d27fbaa0819099f79fc74d211647 |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc14d5688190945f7ae72f724922 |
completed | May 10, 2026, 7:27 p.m. |
| NEDg | Description generation | batch_6a0114d5aeb0819086f1a5d279ac0d0f |
completed | May 10, 2026, 11:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0115c583608190bf07ac205399f253 |
completed | May 10, 2026, 11:33 p.m. |
Created at: April 10, 2026, 5:32 a.m.