Triple
T8066170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trebsen |
E188247
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Trebsen |
E188247
|
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: Trebsen | Statement: [Trebsen, hasSubdivision, Trebsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trebsen Context triple: [Trebsen, hasSubdivision, Trebsen]
-
A.
Trebsen
chosen
Trebsen is a small town in the Free State of Saxony in eastern Germany, known for its historic castle and location along the Mulde River.
-
B.
Tisler
Tisler is a small Norwegian island in the Hvaler archipelago, known for its coastal scenery and traditional seaside cottages.
-
C.
Kremmen
Kremmen is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
-
D.
Kleeberg
Kleeberg is a Polish surname most notably associated with General Franciszek Kleeberg, a commander in the early stages of World War II.
-
E.
Turiec
Turiec is a historical and geographical region in north-central Slovakia, known for its basin landscape surrounded by mountains and the town of Martin as its cultural center.
- 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_69ca82b42674819086840efea12478e5 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ff5547c8190a7ec5958a23e302f |
completed | March 31, 2026, 3:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63e1ed44819083ed9db6c9d7b0fd |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:26 p.m.