Triple
T13691374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unterallgäu |
E328272
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Pfaffenhausen
Pfaffenhausen is a small market town and municipality in the Unterallgäu district of Bavaria, Germany.
|
E1141926
|
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: Pfaffenhausen | Statement: [Unterallgäu, containsMunicipality, Pfaffenhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pfaffenhausen Context triple: [Unterallgäu, containsMunicipality, Pfaffenhausen]
-
A.
Pfeffenhausen
Pfeffenhausen is a market town in Lower Bavaria, Germany, known for its rural character and location within the Landshut district.
-
B.
Eppertshausen
Eppertshausen is a small municipality in the German state of Hesse, located southeast of Frankfurt am Main.
-
C.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
D.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
E.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern 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: Pfaffenhausen Triple: [Unterallgäu, containsMunicipality, Pfaffenhausen]
Generated description
Pfaffenhausen is a small market town and municipality in the Unterallgäu district of Bavaria, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pfaffenhausen Target entity description: Pfaffenhausen is a small market town and municipality in the Unterallgäu district of Bavaria, Germany.
-
A.
Pfeffenhausen
Pfeffenhausen is a market town in Lower Bavaria, Germany, known for its rural character and location within the Landshut district.
-
B.
Eppertshausen
Eppertshausen is a small municipality in the German state of Hesse, located southeast of Frankfurt am Main.
-
C.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
D.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
E.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern 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_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_69fec869957481909ea4fded01851b70 |
completed | May 9, 2026, 5:38 a.m. |
| NEDg | Description generation | batch_69feca4643dc8190af82f6c2f9133e2a |
completed | May 9, 2026, 5:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fecb0459008190888043ab25bae96b |
completed | May 9, 2026, 5:49 a.m. |
Created at: April 9, 2026, 9:53 p.m.