Triple
T4128956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Waldsee |
E84993
|
entity |
| Predicate | locatedBetween |
P1262
|
FINISHED |
| Object |
Bad Wurzach
Bad Wurzach is a spa town in the Allgäu region of southern Germany, known for its moorland landscapes and therapeutic mud baths.
|
E433616
|
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 Wurzach | Statement: [Bad Waldsee, locatedBetween, Bad Wurzach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Wurzach Context triple: [Bad Waldsee, locatedBetween, Bad Wurzach]
-
A.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
B.
Günzburg
Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
-
C.
Bad Cannstatt
Bad Cannstatt is a historic district of Stuttgart, Germany, known for its mineral springs, traditional architecture, and the Cannstatter Volksfest beer festival.
-
D.
Schongau
Schongau is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and location along the Romantic Road.
-
E.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
- 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 Wurzach Triple: [Bad Waldsee, locatedBetween, Bad Wurzach]
Generated description
Bad Wurzach is a spa town in the Allgäu region of southern Germany, known for its moorland landscapes and therapeutic mud baths.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Wurzach Target entity description: Bad Wurzach is a spa town in the Allgäu region of southern Germany, known for its moorland landscapes and therapeutic mud baths.
-
A.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
B.
Günzburg
Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
-
C.
Bad Cannstatt
Bad Cannstatt is a historic district of Stuttgart, Germany, known for its mineral springs, traditional architecture, and the Cannstatter Volksfest beer festival.
-
D.
Schongau
Schongau is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and location along the Romantic Road.
-
E.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af021c5ca48190a829bab07dda55d0 |
completed | March 9, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5db72503c81909e9cf69f23d093fc |
completed | March 14, 2026, 10:04 p.m. |
| NEDg | Description generation | batch_69b5dc0ec2f08190b62711a9abb98099 |
completed | March 14, 2026, 10:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5dca33e0c81909e5047d8bc700530 |
completed | March 14, 2026, 10:09 p.m. |
Created at: March 9, 2026, 3:42 p.m.