Triple
T10442168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fichtel Mountains |
E246194
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Weißenstadt
Weißenstadt is a small Bavarian town in northeastern Germany, known for its scenic lakeside setting and location within the Fichtel Mountains.
|
E912235
|
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: Weißenstadt | Statement: [Fichtel Mountains, hasTown, Weißenstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weißenstadt Context triple: [Fichtel Mountains, hasTown, Weißenstadt]
-
A.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
B.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
-
C.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
D.
Premnitz
Premnitz is a small town in the Havelland region of Brandenburg, Germany, situated on the Havel River and known historically for its chemical industry.
-
E.
Mittenwald
Mittenwald is a picturesque Bavarian town renowned for its traditional violin-making heritage and scenic setting in the German Alps near the Austrian border.
- 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: Weißenstadt Triple: [Fichtel Mountains, hasTown, Weißenstadt]
Generated description
Weißenstadt is a small Bavarian town in northeastern Germany, known for its scenic lakeside setting and location within the Fichtel Mountains.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weißenstadt Target entity description: Weißenstadt is a small Bavarian town in northeastern Germany, known for its scenic lakeside setting and location within the Fichtel Mountains.
-
A.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
B.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
-
C.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
D.
Premnitz
Premnitz is a small town in the Havelland region of Brandenburg, Germany, situated on the Havel River and known historically for its chemical industry.
-
E.
Mittenwald
Mittenwald is a picturesque Bavarian town renowned for its traditional violin-making heritage and scenic setting in the German Alps near the Austrian border.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fb9ebf488190ae776bd65e94cb00 |
completed | April 7, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4aca16a10819097bb8655c8c1a36d |
completed | April 19, 2026, 10:21 a.m. |
| NEDg | Description generation | batch_69e4afa531e0819097587675198bb8a1 |
completed | April 19, 2026, 10:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4b1f68c8c819096d58ac02d76ec0d |
completed | April 19, 2026, 10:44 a.m. |
Created at: April 6, 2026, 12:15 p.m.