Triple
T9440793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augsburg district |
E227639
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Meitingen
Meitingen is a market town in Bavaria, Germany, known as a local industrial and residential center north of the city of Augsburg.
|
E868236
|
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: Meitingen | Statement: [Augsburg district, contains, Meitingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meitingen Context triple: [Augsburg district, contains, Meitingen]
-
A.
Maichingen
Maichingen is a district of the city of Sindelfingen in the German state of Baden-Württemberg.
-
B.
Meißenheim
Meißenheim is a small municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenau district near the Rhine River.
-
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.
Schwabmünchen
Schwabmünchen is a small Bavarian town in southern Germany known for its historic center and location near the city of Augsburg.
-
E.
Metzingen
Metzingen is a town in the German state of Baden-Württemberg, known for its Swabian heritage and large outlet shopping district.
- 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: Meitingen Triple: [Augsburg district, contains, Meitingen]
Generated description
Meitingen is a market town in Bavaria, Germany, known as a local industrial and residential center north of the city of Augsburg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meitingen Target entity description: Meitingen is a market town in Bavaria, Germany, known as a local industrial and residential center north of the city of Augsburg.
-
A.
Maichingen
Maichingen is a district of the city of Sindelfingen in the German state of Baden-Württemberg.
-
B.
Meißenheim
Meißenheim is a small municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenau district near the Rhine River.
-
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.
Schwabmünchen
Schwabmünchen is a small Bavarian town in southern Germany known for its historic center and location near the city of Augsburg.
-
E.
Metzingen
Metzingen is a town in the German state of Baden-Württemberg, known for its Swabian heritage and large outlet shopping district.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee4f4a08190ada5ee14fec2b822 |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90d3dfbac819087d07c35a1776064 |
completed | April 10, 2026, 2:46 p.m. |
| NEDg | Description generation | batch_69d9100604e08190b744b361d60188d5 |
completed | April 10, 2026, 2:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d910a1cdb88190988db41e97341ed9 |
completed | April 10, 2026, 3 p.m. |
Created at: March 30, 2026, 7:50 p.m.