Triple
T10690190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lichtenfels district |
E251989
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Ebensfeld
Ebensfeld is a municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and location along the Main River.
|
E918441
|
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: Ebensfeld | Statement: [Lichtenfels district, hasMunicipality, Ebensfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ebensfeld Context triple: [Lichtenfels district, hasMunicipality, Ebensfeld]
-
A.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
B.
Ochsenfeld
Ochsenfeld is a German surname most notably borne by physicist Robert Ochsenfeld, known for his work on superconductivity.
-
C.
Ebersdorf
Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
-
D.
Premnitz
Premnitz is a small town in the Havelland region of Brandenburg, Germany, situated on the Havel River and known historically for its chemical industry.
-
E.
Ebersberg
Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
- 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: Ebensfeld Triple: [Lichtenfels district, hasMunicipality, Ebensfeld]
Generated description
Ebensfeld is a municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and location along the Main River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ebensfeld Target entity description: Ebensfeld is a municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and location along the Main River.
-
A.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
B.
Ochsenfeld
Ochsenfeld is a German surname most notably borne by physicist Robert Ochsenfeld, known for his work on superconductivity.
-
C.
Ebersdorf
Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
-
D.
Premnitz
Premnitz is a small town in the Havelland region of Brandenburg, Germany, situated on the Havel River and known historically for its chemical industry.
-
E.
Ebersberg
Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd1c0f0081908a6869ee756ec789 |
completed | April 9, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5252da538819091f63ce34709b3b7 |
completed | April 19, 2026, 6:55 p.m. |
| NEDg | Description generation | batch_69e52a78951c8190923711067cf4e7e5 |
completed | April 19, 2026, 7:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5319b6ef0819096debabfb6ffbe70 |
completed | April 19, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:11 p.m.