Triple
T9208393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Weilheim-Schongau |
E221046
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Burggen
Burggen is a small rural municipality in the Bavarian region of Upper Bavaria in southern Germany.
|
E785185
|
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: Burggen | Statement: [District of Weilheim-Schongau, containsMunicipality, Burggen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burggen Context triple: [District of Weilheim-Schongau, containsMunicipality, Burggen]
-
A.
Reideburg
Reideburg is a district of Halle (Saale) in the German state of Saxony-Anhalt, known as the birthplace of prominent politician Hans-Dietrich Genscher.
-
B.
Syrgenstein
Syrgenstein is a small municipality in the Heidenheim district of the German state of Baden-Württemberg.
-
C.
Bocksberg
Bocksberg is a mountain in the Harz region of Germany, known for its hiking trails, winter sports facilities, and scenic views near the village of Hahnenklee.
-
D.
Grimburgwal
Grimburgwal is a historic canal and street in central Amsterdam, known for its picturesque bridges and proximity to the city’s medieval core.
-
E.
Kleeburg
Kleeburg is a historical territory in the Holy Roman Empire that gave its name to the cadet branch of the Wittelsbach dynasty known as the Counts Palatine of Zweibrücken-Kleeburg.
- 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: Burggen Triple: [District of Weilheim-Schongau, containsMunicipality, Burggen]
Generated description
Burggen is a small rural municipality in the Bavarian region of Upper Bavaria in southern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Burggen Target entity description: Burggen is a small rural municipality in the Bavarian region of Upper Bavaria in southern Germany.
-
A.
Reideburg
Reideburg is a district of Halle (Saale) in the German state of Saxony-Anhalt, known as the birthplace of prominent politician Hans-Dietrich Genscher.
-
B.
Syrgenstein
Syrgenstein is a small municipality in the Heidenheim district of the German state of Baden-Württemberg.
-
C.
Bocksberg
Bocksberg is a mountain in the Harz region of Germany, known for its hiking trails, winter sports facilities, and scenic views near the village of Hahnenklee.
-
D.
Grimburgwal
Grimburgwal is a historic canal and street in central Amsterdam, known for its picturesque bridges and proximity to the city’s medieval core.
-
E.
Kleeburg
Kleeburg is a historical territory in the Holy Roman Empire that gave its name to the cadet branch of the Wittelsbach dynasty known as the Counts Palatine of Zweibrücken-Kleeburg.
- 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b217008190a0ab4971dd4a8899 |
completed | April 1, 2026, 8:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d065e967508190acb962d37c390d68 |
completed | April 4, 2026, 1:14 a.m. |
| NEDg | Description generation | batch_69d06770ccf08190b00bf35c16a80071 |
completed | April 4, 2026, 1:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d06864b8c48190b8e08ab9c1c85c9a |
completed | April 4, 2026, 1:24 a.m. |
Created at: March 30, 2026, 7:26 p.m.