Triple
T16064983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U-Bahn line U3 |
E389708
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Krumme Lanke |
E94247
|
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: Krumme Lanke | Statement: [U-Bahn line U3, terminus, Krumme Lanke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krumme Lanke Context triple: [U-Bahn line U3, terminus, Krumme Lanke]
-
A.
Krumme Lanke
chosen
Krumme Lanke is a lake and popular recreational area in southwestern Berlin, known for its wooded surroundings, bathing spots, and walking trails.
-
B.
Treuen
Treuen is a small town in the Vogtland region of Saxony, eastern Germany, known for its historic architecture and rural surroundings.
-
C.
Lanke
Lanke is a village and district within the municipality of Wandlitz in the state of Brandenburg, Germany.
-
D.
Lanke
Lanke is a poetic nickname for the Chinese city of Quzhou, often associated with its cultural heritage and scenic landscapes.
-
E.
Langenes
Langenes is a small coastal village in the former Vågsøy municipality in Vestland county, western Norway.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837bec688190a77ad347600b6bdc |
completed | April 17, 2026, 12:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe47ef6648190bf1fe216e78ef660 |
completed | May 10, 2026, 1:50 a.m. |
Created at: April 10, 2026, 4:57 a.m.