Triple
T12045482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anhalt |
E286774
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Zerbst |
E469155
|
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: Zerbst | Statement: [Anhalt, containsCity, Zerbst]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zerbst Context triple: [Anhalt, containsCity, Zerbst]
-
A.
Zerbst
chosen
Zerbst is a historic town in Saxony-Anhalt, Germany, known as the birthplace of Catherine the Great and for its former role as a princely residence.
-
B.
Jüterbog
Jüterbog is a historic town in the German state of Brandenburg, known for its medieval architecture and long-standing cultural heritage.
-
C.
Anhalt-Zerbst
Anhalt-Zerbst was a small principality within the Holy Roman Empire, historically notable as the homeland of Catherine the Great and a source of German auxiliary troops in the 18th century.
-
D.
Elsterwerda
Elsterwerda is a small town in the state of Brandenburg in eastern Germany, known for its regional railway connections and location near the Elbe-Elster district.
-
E.
Haldensleben
Haldensleben is a town in the German state of Saxony-Anhalt, known as an administrative and economic center with historical roots dating back to the Middle Ages.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9041fe3b0819094b82a6b17ac59c3 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78ac420788190b12167aef7436c64 |
completed | May 3, 2026, 5:49 p.m. |
Created at: April 8, 2026, 9:47 p.m.