Triple
T1266045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unter den Linden |
E15602
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Mitte |
E28609
|
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 | Statement: [Unter den Linden, locatedIn, Mitte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mitte Context triple: [Unter den Linden, locatedIn, Mitte]
-
A.
Mitte
chosen
Mitte is the central district of Berlin, Germany, known as the historic core of the city and home to many major landmarks and government institutions.
-
B.
Middelaar
Middelaar is a village in the Dutch province of Limburg, situated near the river Maas and close to the border with Germany.
-
C.
Midgley
Midgley is a small village in West Yorkshire, England, known for its rural setting in the Calder Valley near Luddenden Foot.
-
D.
Menstrie
Menstrie is a small village in central Scotland, situated at the foot of the Ochil Hills in Clackmannanshire.
-
E.
Melle
Melle is a town in Lower Saxony, Germany, known for its rural character, historical architecture, and role as a regional economic center.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c036deb881909b234894347c75c6 |
completed | March 1, 2026, 10:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac99874f748190bfffe8fb5a649d11 |
completed | March 7, 2026, 9:32 p.m. |
Created at: March 1, 2026, 7:50 p.m.