Triple
T10619384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waremme |
E295667
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Jüterbog |
E490937
|
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: Jüterbog | Statement: [Waremme, hasTwinTown, Jüterbog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jüterbog Context triple: [Waremme, hasTwinTown, Jüterbog]
-
A.
Jüterbog
chosen
Jüterbog is a historic town in the German state of Brandenburg, known for its medieval architecture and long-standing cultural heritage.
-
B.
Zerbst
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.
-
C.
Oranienburg
Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
-
D.
Niederschöneweide
Niederschöneweide is a locality in the Berlin borough of Treptow-Köpenick, known for its riverside setting along the Spree and its mix of residential areas and former industrial sites.
-
E.
Hohen Neuendorf
Hohen Neuendorf is a town in the German state of Brandenburg, located just north of Berlin and known as a residential suburb with access to the capital.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d6df6ee1848190a7d5fcd40b06cfe3 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e37382a0bc81908938b3cbdf0528e0 |
completed | April 18, 2026, 12:05 p.m. |
Created at: April 8, 2026, 8:21 p.m.