Triple
T11029463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Saxon |
E260719
|
entity |
| Predicate | spokenInCity |
P8343
|
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: [Upper Saxon, spokenInCity, Meissen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meissen Context triple: [Upper Saxon, spokenInCity, 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.
Glashütten
Glashütten is a small municipality in the Hochtaunus district of Hesse, Germany, known for its scenic location in the Taunus mountains and its residential, forested character.
-
C.
Meissen district
Meissen district is an administrative district in the Free State of Saxony in eastern Germany, known for its historic towns, wine-growing areas, and proximity to the city of Dresden.
-
D.
Kaisermühlen
Kaisermühlen is a district of Vienna, Austria, known for its modern developments along the Danube and for hosting major international institutions.
-
E.
Abensberg
Abensberg is a historic town in Bavaria, Germany, known for its medieval architecture and its role as a Napoleonic-era battlefield.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d2feb881909a5684721e8b0d9c |
completed | April 9, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3753451e08190bc42ab99d01926f9 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 8, 2026, 9:25 p.m.