Triple
T7792668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werre |
E180218
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Detmold |
E269423
|
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: Detmold | Statement: [Werre, flowsThrough, Detmold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Detmold Context triple: [Werre, flowsThrough, Detmold]
-
A.
Detmold
chosen
Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
-
B.
Lippstadt
Lippstadt is a historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and role in regional conflicts.
-
C.
Meppen
Meppen is a historic town in Lower Saxony, Germany, known as a regional center in the Emsland district near the Dutch border.
-
D.
Gardelegen
Gardelegen is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and its location in the Altmark region.
-
E.
Bielefeld
Bielefeld is a major city in northwestern Germany known for its industrial heritage, university, and the tongue-in-cheek “Bielefeld conspiracy” meme claiming it does not exist.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae938714c8190b89917e6ded004da |
completed | March 30, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d046ccbe588190a0ba7f276d874825 |
completed | April 3, 2026, 11:01 p.m. |
Created at: March 30, 2026, 4:30 p.m.