Triple
T8787871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Traunstein district |
E209087
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
|
E794007
|
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: Trostberg | Statement: [Traunstein district, contains, Trostberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trostberg Context triple: [Traunstein district, contains, Trostberg]
-
A.
Treuchtlingen
Treuchtlingen is a small town in the Bavarian region of Germany, known for its location in the Altmühl Valley and its role as a local railway junction and spa destination.
-
B.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
C.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
D.
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.
-
E.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
- 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: Trostberg Triple: [Traunstein district, contains, Trostberg]
Generated description
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trostberg Target entity description: Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
-
A.
Treuchtlingen
Treuchtlingen is a small town in the Bavarian region of Germany, known for its location in the Altmühl Valley and its role as a local railway junction and spa destination.
-
B.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
C.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
D.
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.
-
E.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f89a84c819085d4cfe4e6dfbda8 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0f3391ff08190a725b0549fb0bc89 |
completed | April 4, 2026, 11:17 a.m. |
| NEDg | Description generation | batch_69d0f46bd034819093e7157a3e1ac1fc |
completed | April 4, 2026, 11:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0f5bf64548190b40e97b279db5105 |
completed | April 4, 2026, 11:27 a.m. |
Created at: March 30, 2026, 6:43 p.m.