Triple
T16381241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soest district |
E397811
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object | Soest |
E175283
|
NE FINISHED |
How this triple was built (2 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: Soest | Statement: [Soest district, containsAdministrativeTerritorialEntity, Soest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soest Context triple: [Soest district, containsAdministrativeTerritorialEntity, Soest]
-
A.
Soest
chosen
Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
-
B.
Soest
Soest is a Dutch town and municipality in the central Netherlands known for its green surroundings and proximity to the Utrechtse Heuvelrug.
-
C.
Voerde
Voerde is a town in the Wesel district of North Rhine-Westphalia, Germany, situated on the Lower Rhine in the Ruhr region.
-
D.
Friesoythe
Friesoythe is a small town in Lower Saxony, Germany, known for its rural character and location within the Cloppenburg district.
-
E.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e319dd0e0c8190812bde6a2f7d9644 |
completed | April 18, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c55bba481909bca6cc17e1dfcf5 |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:08 a.m.