Triple
T15530566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fritz Bleyl |
E370203
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object | Bad Iburg |
E522559
|
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 Iburg | Statement: [Fritz Bleyl, deathPlace, Bad Iburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Iburg Context triple: [Fritz Bleyl, deathPlace, Bad Iburg]
-
A.
Bad Iburg
chosen
Bad Iburg is a small spa town in Lower Saxony, Germany, known for its historic Iburg Castle and surrounding Teutoburg Forest scenery.
-
B.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
C.
Bad Saarow
Bad Saarow is a German spa town in Brandenburg known for its thermal baths and lakeside setting on the Scharmützelsee.
-
D.
Bad Eilsen
Bad Eilsen is a spa town in Lower Saxony, Germany, historically notable for serving as the post–World War II headquarters of the Royal Air Force’s British Air Forces of Occupation.
-
E.
Bad Camberg
Bad Camberg is a German spa town in the state of Hesse, known for its historic half-timbered old town and therapeutic health resorts.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0414773548190b3311515f9d957dd |
completed | April 16, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d5b989c8190a76612df167ba1dd |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:05 a.m.