Triple
T13691372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unterallgäu |
E328272
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Babenhausen
Babenhausen is a market town in the Unterallgäu district of Bavaria, Germany, known for its historic center and role as a local administrative and service hub.
|
E1140220
|
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: Babenhausen | Statement: [Unterallgäu, containsMunicipality, Babenhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Babenhausen Context triple: [Unterallgäu, containsMunicipality, Babenhausen]
-
A.
Babenhausen
Babenhausen is a small town in the German state of Hesse, known for its historic old town and location southeast of Frankfurt am Main.
-
B.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
C.
Beratzhausen
Beratzhausen is a market town in the Upper Palatinate region of Bavaria, Germany, known for its historic center and location in the scenic Laber valley.
-
D.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
E.
Bohnsdorf
Bohnsdorf is a residential locality in the southeastern part of Berlin, Germany, known for its suburban character and proximity to the city’s green and lake-rich areas.
- 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: Babenhausen Triple: [Unterallgäu, containsMunicipality, Babenhausen]
Generated description
Babenhausen is a market town in the Unterallgäu district of Bavaria, Germany, known for its historic center and role as a local administrative and service hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Babenhausen Target entity description: Babenhausen is a market town in the Unterallgäu district of Bavaria, Germany, known for its historic center and role as a local administrative and service hub.
-
A.
Babenhausen
Babenhausen is a small town in the German state of Hesse, known for its historic old town and location southeast of Frankfurt am Main.
-
B.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
C.
Beratzhausen
Beratzhausen is a market town in the Upper Palatinate region of Bavaria, Germany, known for its historic center and location in the scenic Laber valley.
-
D.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
E.
Bohnsdorf
Bohnsdorf is a residential locality in the southeastern part of Berlin, Germany, known for its suburban character and proximity to the city’s green and lake-rich areas.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8746458819095ec1ba3c01ef31b |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfcbbf408190a87f471d2732148b |
completed | May 9, 2026, 5:02 a.m. |
| NEDg | Description generation | batch_69fec21c8e1c8190b2a528acabdf2a49 |
completed | May 9, 2026, 5:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fec2b612c8819084e4601dfff4ad81 |
completed | May 9, 2026, 5:14 a.m. |
Created at: April 9, 2026, 9:53 p.m.