Triple
T9504674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County of Leiningen |
E229232
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Bad Dürkheim |
E505328
|
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 Dürkheim | Statement: [County of Leiningen, hasCapital, Bad Dürkheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Dürkheim Context triple: [County of Leiningen, hasCapital, Bad Dürkheim]
-
A.
Bad Kreuznach
Bad Kreuznach is a historic spa town in western Germany known for its saline springs, medieval architecture, and picturesque location along the Nahe River.
-
B.
Bad Wurzach
Bad Wurzach is a spa town in the Allgäu region of southern Germany, known for its moorland landscapes and therapeutic mud baths.
-
C.
Bad Dürkheim, Germany
chosen
Bad Dürkheim is a spa town in Germany’s Rhineland-Palatinate region, known for its wine production and the annual Wurstmarkt wine festival.
-
D.
Landsberg
Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
-
E.
Meerbusch
Meerbusch is a town in the German state of North Rhine-Westphalia, situated on the west bank of the Rhine near Düsseldorf and known for its affluent residential areas and green surroundings.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9850fe6c8190a5a96cfae12562c6 |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23caf70f8819090ba25c4395c3de2 |
completed | April 5, 2026, 10:42 a.m. |
Created at: March 30, 2026, 7:57 p.m.