Triple
T12567001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Gudensberg
Gudensberg is a small historic town in central Germany known for its medieval architecture and picturesque setting in the state of Hesse.
|
E990704
|
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: Gudensberg | Statement: [Province of Westphalia, containsSettlement, Gudensberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gudensberg Context triple: [Province of Westphalia, containsSettlement, Gudensberg]
-
A.
Gustavsberg
Gustavsberg is a locality in Sweden best known for its historic porcelain factory and role as a suburban community in the Stockholm archipelago.
-
B.
Gundeberga
Gundeberga was a 7th-century Lombard queen consort of Italy, known as the wife of King Rothari.
-
C.
Grönhögen
Grönhögen is a small coastal village on the southern tip of the island of Öland in Sweden, known for its harbor, golf course, and scenic Baltic Sea surroundings.
-
D.
Gogunda
Gogunda is a historic town in Rajasthan, India, known for its association with Maharana Pratap and the Battle of Haldighati.
-
E.
Wästberg
Wästberg is a Swedish surname associated with notable figures in politics, literature, and public life.
- 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: Gudensberg Triple: [Province of Westphalia, containsSettlement, Gudensberg]
Generated description
Gudensberg is a small historic town in central Germany known for its medieval architecture and picturesque setting in the state of Hesse.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gudensberg Target entity description: Gudensberg is a small historic town in central Germany known for its medieval architecture and picturesque setting in the state of Hesse.
-
A.
Gustavsberg
Gustavsberg is a locality in Sweden best known for its historic porcelain factory and role as a suburban community in the Stockholm archipelago.
-
B.
Gundeberga
Gundeberga was a 7th-century Lombard queen consort of Italy, known as the wife of King Rothari.
-
C.
Grönhögen
Grönhögen is a small coastal village on the southern tip of the island of Öland in Sweden, known for its harbor, golf course, and scenic Baltic Sea surroundings.
-
D.
Gogunda
Gogunda is a historic town in Rajasthan, India, known for its association with Maharana Pratap and the Battle of Haldighati.
-
E.
Wästberg
Wästberg is a Swedish surname associated with notable figures in politics, literature, and public life.
- 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_69f655914f908190afbebbec3cb57e73 |
completed | May 2, 2026, 7:50 p.m. |
| NEDg | Description generation | batch_69f657e504c881909b960acc7758b39d |
completed | May 2, 2026, 8 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f658a80fd08190b1b8c161ca6e56ec |
completed | May 2, 2026, 8:03 p.m. |
Created at: April 8, 2026, 11:49 p.m.