Triple
T13691392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unterallgäu |
E328272
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Trunkelsberg
Trunkelsberg is a small municipality in the Unterallgäu district of Bavaria in southern Germany.
|
E1054248
|
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: Trunkelsberg | Statement: [Unterallgäu, containsMunicipality, Trunkelsberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trunkelsberg Context triple: [Unterallgäu, containsMunicipality, Trunkelsberg]
-
A.
Witzmannsberg
Witzmannsberg is a small rural municipality in the Bavarian region of Lower Bavaria, Germany, known for its scenic countryside and traditional village character.
-
B.
Festungsberg
Festungsberg is a prominent hill in Salzburg, Austria, best known as the site of the medieval Hohensalzburg Fortress overlooking the city.
-
C.
Vogelsberg
Vogelsberg is a large volcanic mountain range in the German state of Hesse, known for its forested highlands and rural landscapes.
-
D.
Nonnenstromberg
Nonnenstromberg is a wooded hill in the Siebengebirge range near the Rhine in Germany, known for its natural scenery and hiking trails.
-
E.
Bärenkopf
Bärenkopf is a mountain peak in the Austrian Alps that forms part of the Glockner Group.
- 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: Trunkelsberg Triple: [Unterallgäu, containsMunicipality, Trunkelsberg]
Generated description
Trunkelsberg is a small municipality in the Unterallgäu district of Bavaria in southern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trunkelsberg Target entity description: Trunkelsberg is a small municipality in the Unterallgäu district of Bavaria in southern Germany.
-
A.
Witzmannsberg
Witzmannsberg is a small rural municipality in the Bavarian region of Lower Bavaria, Germany, known for its scenic countryside and traditional village character.
-
B.
Festungsberg
Festungsberg is a prominent hill in Salzburg, Austria, best known as the site of the medieval Hohensalzburg Fortress overlooking the city.
-
C.
Vogelsberg
Vogelsberg is a large volcanic mountain range in the German state of Hesse, known for its forested highlands and rural landscapes.
-
D.
Nonnenstromberg
Nonnenstromberg is a wooded hill in the Siebengebirge range near the Rhine in Germany, known for its natural scenery and hiking trails.
-
E.
Bärenkopf
Bärenkopf is a mountain peak in the Austrian Alps that forms part of the Glockner Group.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8746458819095ec1ba3c01ef31b |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944b93d88190806d6b5735f7e794 |
completed | May 3, 2026, 6:30 p.m. |
| NEDg | Description generation | batch_69f795b1c4948190b3c17acb26cd5b6e |
completed | May 3, 2026, 6:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7965ead2881909a0c33bcc7938543 |
completed | May 3, 2026, 6:39 p.m. |
Created at: April 9, 2026, 9:53 p.m.