Triple
T9010329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landkreis Günzburg |
E215451
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ursberg
Ursberg is a municipality in the Bavarian region of Swabia in southern Germany, known for its rural character and historical monastery complex.
|
E819515
|
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: Ursberg | Statement: [Landkreis Günzburg, contains, Ursberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ursberg Context triple: [Landkreis Günzburg, contains, Ursberg]
-
A.
Johannisberg
Johannisberg is a prominent peak in the Austrian Alps, located in the High Tauern range near the Grossglockner.
-
B.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
C.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
D.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
E.
Ulrichen
Ulrichen is a small alpine village in the Swiss canton of Valais, known for its scenic mountain landscape and outdoor recreation opportunities.
- 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: Ursberg Triple: [Landkreis Günzburg, contains, Ursberg]
Generated description
Ursberg is a municipality in the Bavarian region of Swabia in southern Germany, known for its rural character and historical monastery complex.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ursberg Target entity description: Ursberg is a municipality in the Bavarian region of Swabia in southern Germany, known for its rural character and historical monastery complex.
-
A.
Johannisberg
Johannisberg is a prominent peak in the Austrian Alps, located in the High Tauern range near the Grossglockner.
-
B.
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
C.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
D.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
E.
Ulrichen
Ulrichen is a small alpine village in the Swiss canton of Valais, known for its scenic mountain landscape and outdoor recreation opportunities.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69c00ae8819090786385a72e8baf |
completed | April 1, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bca05c608190935af17d94c567d6 |
completed | April 5, 2026, 1:36 a.m. |
| NEDg | Description generation | batch_69d1bd5820408190a4f5f7ef8b0e14aa |
completed | April 5, 2026, 1:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1bdc0135881909b69814e6cf3741b |
completed | April 5, 2026, 1:41 a.m. |
Created at: March 30, 2026, 7:06 p.m.