Triple
T10075836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lankwitz |
E213752
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Lichterfelde |
E208659
|
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: Lichterfelde | Statement: [Lankwitz, borderedBy, Lichterfelde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lichterfelde Context triple: [Lankwitz, borderedBy, Lichterfelde]
-
A.
Lichterfelde
chosen
Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent character.
-
B.
Mahlsdorf
Mahlsdorf is a locality in the borough of Marzahn-Hellersdorf in eastern Berlin, Germany, known for its residential character and historic village center.
-
C.
Wandlitz
Wandlitz is a municipality in the German state of Brandenburg, known for its lakes, forests, and proximity to Berlin.
-
D.
Degendorf
Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
-
E.
Ludwigsfelde
Ludwigsfelde is a town in the German state of Brandenburg, located just south of Berlin and known for its industrial history and automotive manufacturing.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd0190d808190847ea0fa401ef06c |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d30041f8a88190b24de139e4acf9bb |
completed | April 6, 2026, 12:37 a.m. |
Created at: March 30, 2026, 8:59 p.m.