Triple
T15898954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bautzen district |
E385533
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Doberschau-Gaußig
Doberschau-Gaußig is a municipality in the Bautzen district of Saxony in eastern Germany, known for its rural character and proximity to the city of Bautzen.
|
E1183126
|
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: Doberschau-Gaußig | Statement: [Bautzen district, containsTown, Doberschau-Gaußig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doberschau-Gaußig Context triple: [Bautzen district, containsTown, Doberschau-Gaußig]
-
A.
Doberschütz
Doberschütz is a small municipality in the German state of Saxony that forms part of the broader Leipzig metropolitan area.
-
B.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
C.
Schmedenstedt
Schmedenstedt is a village and district within the town of Peine in Lower Saxony, Germany.
-
D.
Ossenburger
Ossenburger is a wealthy, somewhat comical alumnus of Pencey Prep in J.D. Salinger’s "The Catcher in the Rye," known for donating money to the school and giving a pompous speech to the students.
-
E.
Bernlohe
Bernlohe is a village-level district that forms part of the town of Roth in Bavaria, Germany.
- 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: Doberschau-Gaußig Triple: [Bautzen district, containsTown, Doberschau-Gaußig]
Generated description
Doberschau-Gaußig is a municipality in the Bautzen district of Saxony in eastern Germany, known for its rural character and proximity to the city of Bautzen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Doberschau-Gaußig Target entity description: Doberschau-Gaußig is a municipality in the Bautzen district of Saxony in eastern Germany, known for its rural character and proximity to the city of Bautzen.
-
A.
Doberschütz
Doberschütz is a small municipality in the German state of Saxony that forms part of the broader Leipzig metropolitan area.
-
B.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
C.
Schmedenstedt
Schmedenstedt is a village and district within the town of Peine in Lower Saxony, Germany.
-
D.
Ossenburger
Ossenburger is a wealthy, somewhat comical alumnus of Pencey Prep in J.D. Salinger’s "The Catcher in the Rye," known for donating money to the school and giving a pompous speech to the students.
-
E.
Bernlohe
Bernlohe is a village-level district that forms part of the town of Roth in Bavaria, Germany.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1563bd0688190b6f7a695be0a4625 |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb04d4d1c819091d9b3357ca0deca |
completed | May 9, 2026, 10:08 p.m. |
| NEDg | Description generation | batch_69ffb190ae4881909ac299dfa6e7d9b6 |
completed | May 9, 2026, 10:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb25747148190bc96cf19acf85e29 |
completed | May 9, 2026, 10:16 p.m. |
Created at: April 10, 2026, 4:51 a.m.