Triple
T12567034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Cornberg
Cornberg is a small municipality in the German state of Hesse, known for its rural setting and historical monastery complex.
|
E1052078
|
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: Cornberg | Statement: [Province of Westphalia, containsSettlement, Cornberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cornberg Context triple: [Province of Westphalia, containsSettlement, Cornberg]
-
A.
Stormberg
Stormberg is a mountainous region in South Africa known for its high plateaus, rugged terrain, and significant geological and historical features.
-
B.
Colesberg
Colesberg is a small historic town in South Africa’s Northern Cape, known as a key stopover on the N1 highway and a gateway to the semi-arid Karoo region.
-
C.
Groblersdal
Groblersdal is a town in South Africa’s Limpopo province known as an important agricultural center, particularly for irrigation-based farming.
-
D.
Tulbagh
Tulbagh is a historic town in South Africa’s Western Cape, known for its Cape Dutch architecture and surrounding wine-producing valley.
-
E.
Rustenburg
Rustenburg is a city in South Africa’s North West Province known for its mining industry and as one of the venues for the 2010 FIFA World Cup.
- 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: Cornberg Triple: [Province of Westphalia, containsSettlement, Cornberg]
Generated description
Cornberg is a small municipality in the German state of Hesse, known for its rural setting and historical monastery complex.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cornberg Target entity description: Cornberg is a small municipality in the German state of Hesse, known for its rural setting and historical monastery complex.
-
A.
Stormberg
Stormberg is a mountainous region in South Africa known for its high plateaus, rugged terrain, and significant geological and historical features.
-
B.
Colesberg
Colesberg is a small historic town in South Africa’s Northern Cape, known as a key stopover on the N1 highway and a gateway to the semi-arid Karoo region.
-
C.
Groblersdal
Groblersdal is a town in South Africa’s Limpopo province known as an important agricultural center, particularly for irrigation-based farming.
-
D.
Tulbagh
Tulbagh is a historic town in South Africa’s Western Cape, known for its Cape Dutch architecture and surrounding wine-producing valley.
-
E.
Rustenburg
Rustenburg is a city in South Africa’s North West Province known for its mining industry and as one of the venues for the 2010 FIFA World Cup.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954a325948190994bcfc9d571a3a8 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78ac916748190821c0cdabe54fcbc |
completed | May 3, 2026, 5:50 p.m. |
| NEDg | Description generation | batch_69f78c2e48c48190afb5508beb052af3 |
completed | May 3, 2026, 5:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f78ce2cd50819092654b63acd2c3bf |
completed | May 3, 2026, 5:58 p.m. |
Created at: April 8, 2026, 11:49 p.m.