Triple
T8713380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Passau (district) |
E206834
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Bad Füssing
Bad Füssing is a German spa town in Bavaria renowned for its thermal baths and health tourism.
|
E754922
|
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: Bad Füssing | Statement: [Passau (district), containsMunicipality, Bad Füssing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Füssing Context triple: [Passau (district), containsMunicipality, Bad Füssing]
-
A.
Bad Wörishofen
Bad Wörishofen is a spa town in Bavaria, Germany, renowned as the birthplace of Sebastian Kneipp’s hydrotherapy and wellness treatments.
-
B.
Bad Schussenried
Bad Schussenried is a spa town in southern Germany known for its historic monastery complex and scenic location in Upper Swabia.
-
C.
Bad Salzungen
Bad Salzungen is a spa town in Thuringia, Germany, known for its saline springs and therapeutic health resorts.
-
D.
Bad Mergentheim
Bad Mergentheim is a historic spa town in the German state of Baden-Württemberg, renowned for its mineral springs and picturesque setting in the Tauber Valley.
-
E.
Bad Wiessee
Bad Wiessee is a Bavarian spa town in southern Germany, known for its therapeutic iodine-sulfur springs and scenic location on the shores of Lake Tegernsee.
- 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: Bad Füssing Triple: [Passau (district), containsMunicipality, Bad Füssing]
Generated description
Bad Füssing is a German spa town in Bavaria renowned for its thermal baths and health tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Füssing Target entity description: Bad Füssing is a German spa town in Bavaria renowned for its thermal baths and health tourism.
-
A.
Bad Wörishofen
Bad Wörishofen is a spa town in Bavaria, Germany, renowned as the birthplace of Sebastian Kneipp’s hydrotherapy and wellness treatments.
-
B.
Bad Schussenried
Bad Schussenried is a spa town in southern Germany known for its historic monastery complex and scenic location in Upper Swabia.
-
C.
Bad Salzungen
Bad Salzungen is a spa town in Thuringia, Germany, known for its saline springs and therapeutic health resorts.
-
D.
Bad Mergentheim
Bad Mergentheim is a historic spa town in the German state of Baden-Württemberg, renowned for its mineral springs and picturesque setting in the Tauber Valley.
-
E.
Bad Wiessee
Bad Wiessee is a Bavarian spa town in southern Germany, known for its therapeutic iodine-sulfur springs and scenic location on the shores of Lake Tegernsee.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd522a88190a32facd86206af66 |
completed | March 31, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf42998df88190a6eba28c2efb2030 |
completed | April 3, 2026, 4:31 a.m. |
| NEDg | Description generation | batch_69cf448b65a88190944689160e734866 |
completed | April 3, 2026, 4:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf4578473081909fc55632c366a56a |
completed | April 3, 2026, 4:43 a.m. |
Created at: March 30, 2026, 6:35 p.m.