Triple
T9440794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augsburg district |
E227639
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Gessertshausen
Gessertshausen is a municipality in the Swabian region of Bavaria in southern Germany.
|
E871090
|
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: Gessertshausen | Statement: [Augsburg district, contains, Gessertshausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gessertshausen Context triple: [Augsburg district, contains, Gessertshausen]
-
A.
Weipertshausen
Weipertshausen is a small locality that forms part of the municipality of Münsing in Bavaria, Germany.
-
B.
Gunzenhausen
Gunzenhausen is a historic town in Bavaria, Germany, known for its location on the Altmühl River and as a gateway to the Franconian Lake District.
-
C.
Waigolshausen
Waigolshausen is a small municipality in the Schweinfurt district of Bavaria, Germany, known for its rural character and location in the Franconian region.
-
D.
Assmannshausen
Assmannshausen is a renowned wine-producing village in Germany’s Rheingau region, particularly famous for its red wines made from Spätburgunder (Pinot Noir).
-
E.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
- 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: Gessertshausen Triple: [Augsburg district, contains, Gessertshausen]
Generated description
Gessertshausen is a municipality in the Swabian region of Bavaria in southern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gessertshausen Target entity description: Gessertshausen is a municipality in the Swabian region of Bavaria in southern Germany.
-
A.
Weipertshausen
Weipertshausen is a small locality that forms part of the municipality of Münsing in Bavaria, Germany.
-
B.
Gunzenhausen
Gunzenhausen is a historic town in Bavaria, Germany, known for its location on the Altmühl River and as a gateway to the Franconian Lake District.
-
C.
Waigolshausen
Waigolshausen is a small municipality in the Schweinfurt district of Bavaria, Germany, known for its rural character and location in the Franconian region.
-
D.
Assmannshausen
Assmannshausen is a renowned wine-producing village in Germany’s Rheingau region, particularly famous for its red wines made from Spätburgunder (Pinot Noir).
-
E.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
- 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_69d9330fa33c8190b507ad18362a6c64 |
completed | April 10, 2026, 5:27 p.m. |
| NEDg | Description generation | batch_69d93802a4488190aa86ae209650d4e7 |
completed | April 10, 2026, 5:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d938fcc3c48190a4acaaf75c1aa304 |
completed | April 10, 2026, 5:53 p.m. |
Created at: March 30, 2026, 7:50 p.m.