Triple
T777100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elbe |
E16410
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Meissen |
E74716
|
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: Meissen | Statement: [Elbe, flowsThrough, Meissen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meissen Context triple: [Elbe, flowsThrough, Meissen]
-
A.
Meissen
chosen
Meissen is a historic town in eastern Germany renowned for its medieval architecture and as the birthplace of European hard-paste porcelain.
-
B.
Sorbs
The Sorbs are a Slavic ethnic minority primarily living in eastern Germany, known for preserving their distinct Sorbian language and cultural traditions.
-
C.
Cölln
Cölln was a historic town on the River Spree that, together with Berlin, formed the core of what later became the city of Berlin.
-
D.
Borsigwalde
Borsigwalde is a residential locality in the Berlin borough of Reinickendorf, known for its industrial heritage linked to the Borsig engineering works.
-
E.
Dresden
Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a74da7648190adfad56717d564df |
completed | March 1, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a66d9dd9b48190ba7fae75db01c114 |
completed | March 3, 2026, 5:11 a.m. |
Created at: March 1, 2026, 7:37 p.m.