Triple
T14333870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potsdam-Mittelmark |
E355420
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Bad Belzig
Bad Belzig is a historic spa town in the German state of Brandenburg known for its medieval castle and thermal baths.
|
E1094009
|
NE FINISHED |
How this triple was built (4 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 Belzig | Statement: [Potsdam-Mittelmark, capital, Bad Belzig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Belzig Context triple: [Potsdam-Mittelmark, capital, Bad Belzig]
-
A.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
B.
Bad Oeynhausen
Bad Oeynhausen is a spa town in North Rhine-Westphalia, Germany, renowned for its thermal springs and health resorts.
-
C.
Bad Lauchstädt
Bad Lauchstädt is a historic spa town in the German state of Saxony-Anhalt, known for its classical Kurpark and Goethe-Theater.
-
D.
Bad Düben
Bad Düben is a small spa town in Saxony, Germany, known for its health resorts and location near the Dübener Heide nature park.
-
E.
Bad Elster
Bad Elster is a historic spa town in Saxony, Germany, renowned for its mineral springs and role as a traditional health resort.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bad Belzig Triple: [Potsdam-Mittelmark, capital, Bad Belzig]
Generated description
Bad Belzig is a historic spa town in the German state of Brandenburg known for its medieval castle and thermal baths.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Belzig Target entity description: Bad Belzig is a historic spa town in the German state of Brandenburg known for its medieval castle and thermal baths.
-
A.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
B.
Bad Oeynhausen
Bad Oeynhausen is a spa town in North Rhine-Westphalia, Germany, renowned for its thermal springs and health resorts.
-
C.
Bad Lauchstädt
Bad Lauchstädt is a historic spa town in the German state of Saxony-Anhalt, known for its classical Kurpark and Goethe-Theater.
-
D.
Bad Düben
Bad Düben is a small spa town in Saxony, Germany, known for its health resorts and location near the Dübener Heide nature park.
-
E.
Bad Elster
Bad Elster is a historic spa town in Saxony, Germany, renowned for its mineral springs and role as a traditional health resort.
- F. None of above. chosen
Provenance (5 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c20d2148190bb534bef338e871d |
completed | April 14, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd469634688190980df59ee482b792 |
completed | May 8, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69fd47e2b8d481909ed8274a96615b36 |
completed | May 8, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4879b2688190ac208545ae226c93 |
completed | May 8, 2026, 2:20 a.m. |
Created at: April 10, 2026, 1:13 a.m.