Triple
T16109970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oststadt (Hanover) |
E390846
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Mitte (Hanover) |
E78042
|
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: Mitte (Hanover) | Statement: [Oststadt (Hanover), borderedBy, Mitte (Hanover)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mitte (Hanover) Context triple: [Oststadt (Hanover), borderedBy, Mitte (Hanover)]
-
A.
Mitte, Hanover
chosen
Mitte, Hanover is the central district of the German city of Hanover, encompassing its historic core, main governmental buildings, and key cultural landmarks.
-
B.
Mitte (Leipzig)
Mitte (Leipzig) is the central district of Leipzig, Germany, encompassing the historic city center and key cultural and administrative landmarks.
-
C.
Nordstadt (Hanover)
Nordstadt (Hanover) is a central district of Hanover, Germany, known for its vibrant student population, cultural diversity, and proximity to the university.
-
D.
Oerlinghausen
Oerlinghausen is a small town in the German state of North Rhine-Westphalia, known for its scenic Teutoburg Forest surroundings and historical roots.
-
E.
Northeim
Northeim is a town in Lower Saxony, Germany, known for its medieval old town and location in the Leine River valley.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2016665c0819081aa7a44b1d08183 |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeba674788190a589104cf90f28d5 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 5 a.m.