Triple
T20729933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freudenstadt (district) |
E509545
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Loßburg
Loßburg is a municipality in the Black Forest region of southwestern Germany, known for its scenic landscapes and traditional Swabian character.
|
E1448286
|
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: Loßburg | Statement: [Freudenstadt (district), hasMunicipality, Loßburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loßburg Context triple: [Freudenstadt (district), hasMunicipality, Loßburg]
-
A.
Artlenburg
Artlenburg is a small municipality in northern Germany, situated on the Elbe River in the state of Lower Saxony.
-
B.
Lossberg
Lossberg is a German surname most notably associated with the military strategist Fritz von Lossberg of the Imperial German Army during World War I.
-
C.
Arzdorf
Arzdorf is a village and district of the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
D.
Valkhof
Valkhof is a historic site in Nijmegen, Netherlands, known for its hilltop park and medieval castle ruins overlooking the River Waal.
-
E.
Mörlheim
Mörlheim is a district of the town Landau in der Pfalz in the state of Rhineland-Palatinate, 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: Loßburg Triple: [Freudenstadt (district), hasMunicipality, Loßburg]
Generated description
Loßburg is a municipality in the Black Forest region of southwestern Germany, known for its scenic landscapes and traditional Swabian character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Loßburg Target entity description: Loßburg is a municipality in the Black Forest region of southwestern Germany, known for its scenic landscapes and traditional Swabian character.
-
A.
Artlenburg
Artlenburg is a small municipality in northern Germany, situated on the Elbe River in the state of Lower Saxony.
-
B.
Lossberg
Lossberg is a German surname most notably associated with the military strategist Fritz von Lossberg of the Imperial German Army during World War I.
-
C.
Arzdorf
Arzdorf is a village and district of the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
D.
Valkhof
Valkhof is a historic site in Nijmegen, Netherlands, known for its hilltop park and medieval castle ruins overlooking the River Waal.
-
E.
Mörlheim
Mörlheim is a district of the town Landau in der Pfalz in the state of Rhineland-Palatinate, 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1ec9820819093a07f90503686b2 |
completed | April 21, 2026, 12:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08e8358878819093b928e3dc4a9f69 |
completed | May 16, 2026, 9:57 p.m. |
| NEDg | Description generation | batch_6a08e91f9e648190a39d1ff3dc3ca040 |
completed | May 16, 2026, 10:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08e9d349e88190b3fb6b30744df6c5 |
completed | May 16, 2026, 10:04 p.m. |
Created at: April 16, 2026, 12:30 p.m.