Triple
T6201406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bezirk Rostock |
E138640
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Bad Doberan
Bad Doberan is a historic spa town in northern Germany known for its medieval Doberan Minster and proximity to the Baltic Sea coast.
|
E575884
|
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 Doberan | Statement: [Bezirk Rostock, contains, Bad Doberan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Doberan Context triple: [Bezirk Rostock, contains, Bad Doberan]
-
A.
Bad Oeynhausen
Bad Oeynhausen is a spa town in North Rhine-Westphalia, Germany, renowned for its thermal springs and health resorts.
-
B.
Bad Segeberg
Bad Segeberg is a small spa town in northern Germany best known for its limestone caves and annual Karl May Festival.
-
C.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
D.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
E.
Bad Tölz
Bad Tölz is a Bavarian spa town in southern Germany known for its historic old town, alpine scenery, and traditional German architecture.
- 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 Doberan Triple: [Bezirk Rostock, contains, Bad Doberan]
Generated description
Bad Doberan is a historic spa town in northern Germany known for its medieval Doberan Minster and proximity to the Baltic Sea coast.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Doberan Target entity description: Bad Doberan is a historic spa town in northern Germany known for its medieval Doberan Minster and proximity to the Baltic Sea coast.
-
A.
Bad Oeynhausen
Bad Oeynhausen is a spa town in North Rhine-Westphalia, Germany, renowned for its thermal springs and health resorts.
-
B.
Bad Segeberg
Bad Segeberg is a small spa town in northern Germany best known for its limestone caves and annual Karl May Festival.
-
C.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
D.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
E.
Bad Tölz
Bad Tölz is a Bavarian spa town in southern Germany known for its historic old town, alpine scenery, and traditional German architecture.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062559bcc81908942bb4d25fe8158 |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f366cfc81909cca73677268821a |
completed | March 23, 2026, 4:49 p.m. |
| NEDg | Description generation | batch_69c1e375c5948190ad166089e866694a |
completed | March 24, 2026, 1:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1e43fa8348190a2247996d88b5011 |
completed | March 24, 2026, 1:09 a.m. |
Created at: March 22, 2026, 4:20 p.m.