Triple
T568681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin U-Bahn line U6 |
E13613
|
entity |
| Predicate | connectsDistrict |
P2564
|
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: [Berlin U-Bahn line U6, connectsDistrict, Mitte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mitte Context triple: [Berlin U-Bahn line U6, connectsDistrict, 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.
Middleton
Middleton is a village and civil parish in the English county of Norfolk, situated near the town of King’s Lynn.
-
C.
Middleton
Middleton is a town in Greater Manchester, England, historically part of Lancashire and now a residential and industrial suburb of Manchester.
-
D.
Sentrum
Sentrum is the central district of Oslo, Norway, which hosts some of the University of Oslo’s urban campus facilities.
-
E.
Stadtmitte
Stadtmitte is a central Berlin U-Bahn station serving as an important interchange and access point to the city’s historic Mitte district.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b0406d481908af5fc7bc67103fb |
completed | March 1, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4fc81d6d4819090d91560efaa085d |
completed | March 2, 2026, 2:57 a.m. |
Created at: March 1, 2026, 7:33 p.m.