Triple
T14367192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augustusplatz |
E356265
|
entity |
| Predicate | locatedInDistrict |
P40
|
FINISHED |
| Object |
Mitte (Leipzig)
Mitte (Leipzig) is the central district of Leipzig, Germany, encompassing the historic city center and key cultural and administrative landmarks.
|
E1095144
|
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: Mitte (Leipzig) | Statement: [Augustusplatz, locatedInDistrict, Mitte (Leipzig)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mitte (Leipzig) Context triple: [Augustusplatz, locatedInDistrict, Mitte (Leipzig)]
-
A.
Mitte, Berlin
Mitte, Berlin is the central district of Germany’s capital city, known for its historic core, major cultural institutions, and many of Berlin’s most famous landmarks.
-
B.
Roßdorf
Roßdorf is a municipality in the German state of Hesse, located near the city of Darmstadt.
-
C.
Mahlsdorf
Mahlsdorf is a locality in the borough of Marzahn-Hellersdorf in eastern Berlin, Germany, known for its residential character and historic village center.
-
D.
Beuel-Mitte
Beuel-Mitte is the central district of the Beuel borough in Bonn, Germany, serving as its main urban and commercial area.
-
E.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in 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: Mitte (Leipzig) Triple: [Augustusplatz, locatedInDistrict, Mitte (Leipzig)]
Generated description
Mitte (Leipzig) is the central district of Leipzig, Germany, encompassing the historic city center and key cultural and administrative landmarks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mitte (Leipzig) Target entity description: Mitte (Leipzig) is the central district of Leipzig, Germany, encompassing the historic city center and key cultural and administrative landmarks.
-
A.
Mitte, Berlin
Mitte, Berlin is the central district of Germany’s capital city, known for its historic core, major cultural institutions, and many of Berlin’s most famous landmarks.
-
B.
Roßdorf
Roßdorf is a municipality in the German state of Hesse, located near the city of Darmstadt.
-
C.
Mahlsdorf
Mahlsdorf is a locality in the borough of Marzahn-Hellersdorf in eastern Berlin, Germany, known for its residential character and historic village center.
-
D.
Beuel-Mitte
Beuel-Mitte is the central district of the Beuel borough in Bonn, Germany, serving as its main urban and commercial area.
-
E.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8faf00e8819087d7100e9d8c1877 |
completed | April 14, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c4fa3788190b7fa5c34620c3ada |
completed | May 8, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fd4e14f4dc8190860bd3bd4e306e28 |
completed | May 8, 2026, 2:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4ea9fefc8190a5650f8ee270f37f |
completed | May 8, 2026, 2:47 a.m. |
Created at: April 10, 2026, 1:15 a.m.