Triple
T22777436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ziegelgraben Bridge |
E563740
|
entity |
| Predicate | crosses |
P416
|
FINISHED |
| Object |
Ziegelgraben
Ziegelgraben is a waterway in northern Germany that serves as a navigable channel between parts of the Baltic Sea near Stralsund.
|
E1553746
|
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: Ziegelgraben | Statement: [Ziegelgraben Bridge, crosses, Ziegelgraben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ziegelgraben Context triple: [Ziegelgraben Bridge, crosses, Ziegelgraben]
-
A.
Frauentorgraben
Frauentorgraben is a major street and section of the historic defensive moat encircling Nuremberg’s old town in Bavaria, Germany.
-
B.
Kreuzlinger Forstgraben
Kreuzlinger Forstgraben is a small watercourse in Bavaria that serves as one of the tributary streams feeding into Lake Starnberg.
-
C.
Rohrbachgraben
Rohrbachgraben is a small rural municipality in the Oberaargau region of the canton of Bern in Switzerland.
-
D.
Tiefgraben
Tiefgraben is a municipality in the Austrian state of Upper Austria, known for its scenic lakeside setting near Mondsee.
-
E.
St. Alban-Graben
St. Alban-Graben is a central street in Basel, Switzerland, known for hosting major cultural institutions and serving as an important urban thoroughfare.
- 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: Ziegelgraben Triple: [Ziegelgraben Bridge, crosses, Ziegelgraben]
Generated description
Ziegelgraben is a waterway in northern Germany that serves as a navigable channel between parts of the Baltic Sea near Stralsund.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ziegelgraben Target entity description: Ziegelgraben is a waterway in northern Germany that serves as a navigable channel between parts of the Baltic Sea near Stralsund.
-
A.
Frauentorgraben
Frauentorgraben is a major street and section of the historic defensive moat encircling Nuremberg’s old town in Bavaria, Germany.
-
B.
Kreuzlinger Forstgraben
Kreuzlinger Forstgraben is a small watercourse in Bavaria that serves as one of the tributary streams feeding into Lake Starnberg.
-
C.
Rohrbachgraben
Rohrbachgraben is a small rural municipality in the Oberaargau region of the canton of Bern in Switzerland.
-
D.
Tiefgraben
Tiefgraben is a municipality in the Austrian state of Upper Austria, known for its scenic lakeside setting near Mondsee.
-
E.
St. Alban-Graben
St. Alban-Graben is a central street in Basel, Switzerland, known for hosting major cultural institutions and serving as an important urban thoroughfare.
- 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_69e24554497c819080b996e071de27c2 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b6260a8819080e57481281dfe40 |
completed | April 29, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b9824f4108190b430ea2138a57ba0 |
completed | May 18, 2026, 10:52 p.m. |
| NEDg | Description generation | batch_6a0b9970f0388190a71f234f8022fc3e |
completed | May 18, 2026, 10:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9a1129c8819084163353accc7e14 |
completed | May 18, 2026, 11 p.m. |
Created at: April 17, 2026, 3:28 p.m.