Triple
T8600818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landkreis Biberach |
E203668
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Bad Wurzach |
E433616
|
NE FINISHED |
How this triple was built (2 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: [Landkreis Biberach, hasMunicipality, Bad Wurzach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Wurzach Context triple: [Landkreis Biberach, hasMunicipality, Bad Wurzach]
-
A.
Bad Wurzach
chosen
Bad Wurzach is a spa town in the Allgäu region of southern Germany, known for its moorland landscapes and therapeutic mud baths.
-
B.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
C.
Günzburg
Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
-
D.
Bad Cannstatt
Bad Cannstatt is a historic district of Stuttgart, Germany, known for its mineral springs, traditional architecture, and the Cannstatter Volksfest beer festival.
-
E.
Alzey
Alzey is a historic town in the Rhineland-Palatinate region of Germany, known as one of the Nibelungen cities and for its wine-growing tradition.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46d8ff408190acc7cd8dc99b2689 |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef33f0aa0819091e101f822c53c0f |
completed | April 2, 2026, 10:52 p.m. |
Created at: March 30, 2026, 6:24 p.m.