Triple
T18128330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weißenburg-Gunzenhausen |
E433941
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Pappenheim |
—
|
NE NERFINISHED |
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: Pappenheim | Statement: [Weißenburg-Gunzenhausen, contains, Pappenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pappenheim Context triple: [Weißenburg-Gunzenhausen, contains, Pappenheim]
-
A.
Pappenheim
chosen
Pappenheim is a historic market town in Bavaria, Germany, known for its medieval architecture and its location along the Altmühl River.
-
B.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
-
C.
Kottenheim
Kottenheim is a small municipality in western Germany’s Rhineland-Palatinate region, known for its volcanic landscape and traditional stone quarrying.
-
D.
Neudrossenfeld
Neudrossenfeld is a municipality in the Kulmbach district of northern Bavaria, Germany, known for its rural character and Franconian cultural heritage.
-
E.
Meisenthal
Meisenthal is a village in northeastern France renowned for its historic glassmaking tradition and cultural heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddf061b48190b67356f1c266b80a |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:29 a.m.