Triple
T2177037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saxony-Anhalt |
E48552
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Quedlinburg |
E95916
|
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: Quedlinburg | Statement: [Saxony-Anhalt, contains, Quedlinburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quedlinburg Context triple: [Saxony-Anhalt, contains, Quedlinburg]
-
A.
Quedlinburg
chosen
Quedlinburg is a historic German town on the northern edge of the Harz mountains, renowned for its well-preserved medieval architecture and UNESCO World Heritage–listed old town.
-
B.
Wolfenbüttel
Wolfenbüttel is a historic town in Lower Saxony, Germany, known for its Renaissance castle and rich cultural heritage.
-
C.
Wernigerode
Wernigerode is a picturesque German town in Saxony-Anhalt known for its colorful half-timbered houses, medieval castle, and location on the northern slopes of the Harz Mountains.
-
D.
Naumburg
Naumburg is a historic town in the German state of Saxony-Anhalt, known for its medieval cathedral and as the childhood home of philosopher Friedrich Nietzsche.
-
E.
Hanover
Hanover is a small New Hampshire town best known as the home of Dartmouth College, an Ivy League institution.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbeecdbc881909982a58568f0b1ed |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5da14e3881909f0beda339599938 |
completed | March 9, 2026, 5:41 a.m. |
Created at: March 4, 2026, 7:45 p.m.