Triple
T12566995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Gilserberg
Gilserberg is a small municipality in the German state of Hesse, known for its rural character and location within the Schwalm-Eder district.
|
E990701
|
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: Gilserberg | Statement: [Province of Westphalia, containsSettlement, Gilserberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gilserberg Context triple: [Province of Westphalia, containsSettlement, Gilserberg]
-
A.
Spiegelberg
Spiegelberg is a rebellious and scheming member of the robber band in Friedrich Schiller’s play "Die Räuber," known for his ruthless ambition and treacherous nature.
-
B.
Syrgenstein
Syrgenstein is a small municipality in the Heidenheim district of the German state of Baden-Württemberg.
-
C.
Hesselberg
Hesselberg is a prominent hill in Bavaria, Germany, known as the highest elevation of the Franconian Alb region.
-
D.
Seelenberg
Seelenberg is a small village that forms one of the local subdivisions of the municipality of Schmitten in Germany.
-
E.
Wolfisberg
Wolfisberg is a small Swiss municipality in the canton of Bern, known for its rural setting in the Oberaargau region.
- 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: Gilserberg Triple: [Province of Westphalia, containsSettlement, Gilserberg]
Generated description
Gilserberg is a small municipality in the German state of Hesse, known for its rural character and location within the Schwalm-Eder district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gilserberg Target entity description: Gilserberg is a small municipality in the German state of Hesse, known for its rural character and location within the Schwalm-Eder district.
-
A.
Spiegelberg
Spiegelberg is a rebellious and scheming member of the robber band in Friedrich Schiller’s play "Die Räuber," known for his ruthless ambition and treacherous nature.
-
B.
Syrgenstein
Syrgenstein is a small municipality in the Heidenheim district of the German state of Baden-Württemberg.
-
C.
Hesselberg
Hesselberg is a prominent hill in Bavaria, Germany, known as the highest elevation of the Franconian Alb region.
-
D.
Seelenberg
Seelenberg is a small village that forms one of the local subdivisions of the municipality of Schmitten in Germany.
-
E.
Wolfisberg
Wolfisberg is a small Swiss municipality in the canton of Bern, known for its rural setting in the Oberaargau region.
- 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.