Triple
T10923427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friedrichshafen |
E258002
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object |
Delitzsch
Delitzsch is a historic town in the German state of Saxony, known for its well-preserved medieval center and regional administrative role.
|
E941236
|
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: Delitzsch | Statement: [Friedrichshafen, twinnedWith, Delitzsch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Delitzsch Context triple: [Friedrichshafen, twinnedWith, Delitzsch]
-
A.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
B.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
C.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
D.
Dennewitz
Dennewitz is a village in Brandenburg, Germany, historically notable as the site of a major 1813 battle during the Napoleonic Wars.
-
E.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
- 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: Delitzsch Triple: [Friedrichshafen, twinnedWith, Delitzsch]
Generated description
Delitzsch is a historic town in the German state of Saxony, known for its well-preserved medieval center and regional administrative role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Delitzsch Target entity description: Delitzsch is a historic town in the German state of Saxony, known for its well-preserved medieval center and regional administrative role.
-
A.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
B.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
C.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
D.
Dennewitz
Dennewitz is a village in Brandenburg, Germany, historically notable as the site of a major 1813 battle during the Napoleonic Wars.
-
E.
Trostberg
Trostberg is a small Bavarian town in southeastern Germany known for its historic old town and chemical industry.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7708e3fd881908da10f24a856364c |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef8185c6e08190949020a80c24f2b8 |
completed | April 27, 2026, 3:32 p.m. |
| NEDg | Description generation | batch_69ef96ab29d48190b225504856007384 |
completed | April 27, 2026, 5:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69efd64bfa7081909715aa64d80fadf3 |
completed | April 27, 2026, 9:34 p.m. |
Created at: April 8, 2026, 9:22 p.m.