Triple
T22319579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thierstein district |
E551745
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Meltingen
Meltingen is a small Swiss municipality located in the canton of Solothurn.
|
E1531761
|
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: Meltingen | Statement: [Thierstein district, containsMunicipality, Meltingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meltingen Context triple: [Thierstein district, containsMunicipality, Meltingen]
-
A.
Molndal
Mölndal is a Swedish city in Västra Götaland County, just south of Gothenburg, known for its industrial heritage and proximity to major research and technology hubs.
-
B.
Mellingen
Mellingen is a small Swiss town in the canton of Aargau known for its historic old town and riverside setting along the Reuss.
-
C.
Mellingen
Mellingen is a small municipality in the German state of Thuringia, known for its location near the historic city of Weimar.
-
D.
Rudersberg
Rudersberg is a small municipality in the German state of Baden-Württemberg, situated in the Rems-Murr district near the city of Stuttgart.
-
E.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
- 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: Meltingen Triple: [Thierstein district, containsMunicipality, Meltingen]
Generated description
Meltingen is a small Swiss municipality located in the canton of Solothurn.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meltingen Target entity description: Meltingen is a small Swiss municipality located in the canton of Solothurn.
-
A.
Molndal
Mölndal is a Swedish city in Västra Götaland County, just south of Gothenburg, known for its industrial heritage and proximity to major research and technology hubs.
-
B.
Mellingen
Mellingen is a small Swiss town in the canton of Aargau known for its historic old town and riverside setting along the Reuss.
-
C.
Mellingen
Mellingen is a small municipality in the German state of Thuringia, known for its location near the historic city of Weimar.
-
D.
Rudersberg
Rudersberg is a small municipality in the German state of Baden-Württemberg, situated in the Rems-Murr district near the city of Stuttgart.
-
E.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15762fac08190a6a514baffbbbca1 |
completed | April 29, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ad5174c20819090b3f7ffd85a8376 |
completed | May 18, 2026, 9 a.m. |
| NEDg | Description generation | batch_6a0ad991a1e48190ad240a20694223fc |
completed | May 18, 2026, 9:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ada2a61b881908a636b2d1d6e4509 |
completed | May 18, 2026, 9:21 a.m. |
Created at: April 16, 2026, 8:42 p.m.