Triple
T10629752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Möhnesee |
E250420
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Theiningsen |
E684026
|
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: Theiningsen | Statement: [Möhnesee, hasPart, Theiningsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Theiningsen Context triple: [Möhnesee, hasPart, Theiningsen]
-
A.
Thöningsen
Thöningsen is a village-level district that forms part of the town of Soest in North Rhine-Westphalia, Germany.
-
B.
Deiringsen
chosen
Deiringsen is a village and district within the town of Soest in North Rhine-Westphalia, Germany.
-
C.
Tingleff
Tingleff is a small town in southern Denmark, historically part of the Schleswig region near the German border.
-
D.
Holthees
Holthees is a small village in the Dutch province of North Brabant, known for its rural character and historic church.
-
E.
Gyllensten
Gyllensten is a Swedish surname most notably associated with Lars Gyllensten, a prominent author and former member of the Swedish Academy.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df92f8388190a8bcff96809d8eb4 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96babc290819096c0c914d038ba01 |
completed | April 10, 2026, 9:29 p.m. |
Created at: April 8, 2026, 9 p.m.