Triple
T7295866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heidekreis |
E164519
|
entity |
| Predicate | administrativeSeat |
P21613
|
FINISHED |
| Object | Bad Fallingbostel |
E430089
|
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 Fallingbostel | Statement: [Heidekreis, administrativeSeat, Bad Fallingbostel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Fallingbostel Context triple: [Heidekreis, administrativeSeat, Bad Fallingbostel]
-
A.
Fallingbostel
chosen
Fallingbostel is a town in Lower Saxony, Germany, historically known for its military installations and role as a British Army garrison location after World War II.
-
B.
Bad Bramstedt
Bad Bramstedt is a small spa town in northern Germany’s Schleswig-Holstein region, known for its therapeutic clinics and tranquil rural setting.
-
C.
Bad Bentheim
Bad Bentheim is a historic spa town in Lower Saxony, Germany, best known for its medieval Bentheim Castle and therapeutic mineral springs.
-
D.
Bad Segeberg
Bad Segeberg is a small spa town in northern Germany best known for its limestone caves and annual Karl May Festival.
-
E.
Bad Oeynhausen
Bad Oeynhausen is a spa town in North Rhine-Westphalia, Germany, renowned for its thermal springs and 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8d0c6c8190b32cd08b9a5d96cc |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eee330e08190b39bdf3f5071cace |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 3 p.m.