Triple
T8713387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Passau (district) |
E206834
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
|
E792279
|
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: Fürstenzell | Statement: [Passau (district), containsMunicipality, Fürstenzell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fürstenzell Context triple: [Passau (district), containsMunicipality, Fürstenzell]
-
A.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
-
B.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
-
C.
Ötlingen
Ötlingen is a village-like district of the town of Weil am Rhein in the southwestern German state of Baden-Württemberg, near the borders with France and Switzerland.
-
D.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
E.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
- 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: Fürstenzell Triple: [Passau (district), containsMunicipality, Fürstenzell]
Generated description
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fürstenzell Target entity description: Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
A.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
-
B.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
-
C.
Ötlingen
Ötlingen is a village-like district of the town of Weil am Rhein in the southwestern German state of Baden-Württemberg, near the borders with France and Switzerland.
-
D.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
E.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd522a88190a32facd86206af66 |
completed | March 31, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e2df0a988190a23a87dff30af98f |
completed | April 4, 2026, 10:07 a.m. |
| NEDg | Description generation | batch_69d0e502b68081909a9f9476421ba9b5 |
completed | April 4, 2026, 10:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0e5af7360819096c6295de0ce5f32 |
completed | April 4, 2026, 10:19 a.m. |
Created at: March 30, 2026, 6:35 p.m.