Triple
T6032200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hochsauerlandkreis |
E134331
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Hallenberg
Hallenberg is a small town and municipality in the Hochsauerland district of North Rhine-Westphalia, Germany, known for its scenic location in the Sauerland region.
|
E564064
|
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: Hallenberg | Statement: [Hochsauerlandkreis, containsMunicipality, Hallenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hallenberg Context triple: [Hochsauerlandkreis, containsMunicipality, Hallenberg]
-
A.
Haldenstein
Haldenstein is a small Swiss village in the canton of Graubünden, known in architecture circles as the longtime base of renowned architect Peter Zumthor.
-
B.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
C.
Haller
Haller is a surname most notably associated with Ernest Haller, an American cinematographer renowned for his work in classic Hollywood films.
-
D.
Erasbach
Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
-
E.
Hellenstein
Hellenstein is the historical namesake associated with Hellenstein Castle, a prominent medieval fortress in Heidenheim, Germany.
- 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: Hallenberg Triple: [Hochsauerlandkreis, containsMunicipality, Hallenberg]
Generated description
Hallenberg is a small town and municipality in the Hochsauerland district of North Rhine-Westphalia, Germany, known for its scenic location in the Sauerland region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hallenberg Target entity description: Hallenberg is a small town and municipality in the Hochsauerland district of North Rhine-Westphalia, Germany, known for its scenic location in the Sauerland region.
-
A.
Haldenstein
Haldenstein is a small Swiss village in the canton of Graubünden, known in architecture circles as the longtime base of renowned architect Peter Zumthor.
-
B.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
C.
Haller
Haller is a surname most notably associated with Ernest Haller, an American cinematographer renowned for his work in classic Hollywood films.
-
D.
Erasbach
Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
-
E.
Hellenstein
Hellenstein is the historical namesake associated with Hellenstein Castle, a prominent medieval fortress in Heidenheim, Germany.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b0a8d081909035e2e85e851ca1 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c113855ad08190b9ff826a2f39c356 |
completed | March 23, 2026, 10:18 a.m. |
| NEDg | Description generation | batch_69c114ec9d0c819092de76a6712c482d |
completed | March 23, 2026, 10:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c115552c188190b500d96e86410180 |
completed | March 23, 2026, 10:26 a.m. |
Created at: March 22, 2026, 4:08 p.m.