Triple
T15898945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bautzen district |
E385533
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Haselbachtal
Haselbachtal is a municipality in the German state of Saxony, known for its rural character and location within the Bautzen district.
|
E1184031
|
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: Haselbachtal | Statement: [Bautzen district, containsTown, Haselbachtal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haselbachtal Context triple: [Bautzen district, containsTown, Haselbachtal]
-
A.
Fischbachtal
Fischbachtal is a small municipality in southern Hesse, Germany, known for its rural landscape and the historic Lichtenberg Castle.
-
B.
Urbachtal
Urbachtal is a remote alpine valley in the Bernese Oberland region of Switzerland, known for its rugged mountain scenery and hiking routes.
-
C.
Münstertal
Münstertal is a picturesque municipality in Germany’s Black Forest region, known for its scenic valley landscapes and traditional rural character.
-
D.
Löstertal
Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
-
E.
Käbschütztal
Käbschütztal is a rural municipality in the Free State of Saxony in eastern Germany, characterized by its agricultural landscape and small village communities.
- 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: Haselbachtal Triple: [Bautzen district, containsTown, Haselbachtal]
Generated description
Haselbachtal is a municipality in the German state of Saxony, known for its rural character and location within the Bautzen district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Haselbachtal Target entity description: Haselbachtal is a municipality in the German state of Saxony, known for its rural character and location within the Bautzen district.
-
A.
Fischbachtal
Fischbachtal is a small municipality in southern Hesse, Germany, known for its rural landscape and the historic Lichtenberg Castle.
-
B.
Urbachtal
Urbachtal is a remote alpine valley in the Bernese Oberland region of Switzerland, known for its rugged mountain scenery and hiking routes.
-
C.
Münstertal
Münstertal is a picturesque municipality in Germany’s Black Forest region, known for its scenic valley landscapes and traditional rural character.
-
D.
Löstertal
Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
-
E.
Käbschütztal
Käbschütztal is a rural municipality in the Free State of Saxony in eastern Germany, characterized by its agricultural landscape and small village communities.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1563bd0688190b6f7a695be0a4625 |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5a1b1548190a8579cebf9e71121 |
completed | May 9, 2026, 10:30 p.m. |
| NEDg | Description generation | batch_69ffb62f3d8881908ede4a9a4b53bef2 |
completed | May 9, 2026, 10:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb6f3154481909632913f4d7cfdba |
completed | May 9, 2026, 10:36 p.m. |
Created at: April 10, 2026, 4:51 a.m.