Triple
T8020377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unstrut River region |
E186724
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Bad Tennstedt
Bad Tennstedt is a small spa town in Thuringia, Germany, known for its mineral springs and location in the Unstrut river landscape.
|
E708764
|
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 Tennstedt | Statement: [Unstrut River region, contains, Bad Tennstedt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Tennstedt Context triple: [Unstrut River region, contains, Bad Tennstedt]
-
A.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
B.
Bad Brambach
Bad Brambach is a German spa town in the Vogtland region of Saxony, renowned for its mineral springs and therapeutic health resorts.
-
C.
Bad Mergentheim
Bad Mergentheim is a historic spa town in the German state of Baden-Württemberg, renowned for its mineral springs and picturesque setting in the Tauber Valley.
-
D.
Bad Frankenhausen
Bad Frankenhausen is a small spa town in the German state of Thuringia, known for its saline springs and the nearby Kyffhäuser hills.
-
E.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
- 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 Tennstedt Triple: [Unstrut River region, contains, Bad Tennstedt]
Generated description
Bad Tennstedt is a small spa town in Thuringia, Germany, known for its mineral springs and location in the Unstrut river landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Tennstedt Target entity description: Bad Tennstedt is a small spa town in Thuringia, Germany, known for its mineral springs and location in the Unstrut river landscape.
-
A.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
B.
Bad Brambach
Bad Brambach is a German spa town in the Vogtland region of Saxony, renowned for its mineral springs and therapeutic health resorts.
-
C.
Bad Mergentheim
Bad Mergentheim is a historic spa town in the German state of Baden-Württemberg, renowned for its mineral springs and picturesque setting in the Tauber Valley.
-
D.
Bad Frankenhausen
Bad Frankenhausen is a small spa town in the German state of Thuringia, known for its saline springs and the nearby Kyffhäuser hills.
-
E.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e8d90488190b57d1e748e272061 |
completed | March 31, 2026, 3:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56c82824819082e93eddc40bfad1 |
completed | March 31, 2026, 11:20 p.m. |
| NEDg | Description generation | batch_69cc5ca6efbc819082f4c643446da354 |
completed | March 31, 2026, 11:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc5d6d93f08190b17d6c7a4fad2cf0 |
completed | March 31, 2026, 11:49 p.m. |
Created at: March 30, 2026, 5:20 p.m.