Triple
T5522409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin U-Bahn |
E144841
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object | U9 |
E353649
|
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: U9 | Statement: [Berlin U-Bahn, hasLine, U9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: U9 Context triple: [Berlin U-Bahn, hasLine, U9]
-
A.
U9
chosen
U9 is a Berlin U-Bahn subway line that serves the Wedding district among other areas in the city.
-
B.
U7
U7 is a line of the Berlin U-Bahn rapid transit system, running in an east–west direction across the city.
-
C.
U-17
U-17 is a youth football age category for players under 17 years old, commonly used in international and domestic competitions.
-
D.
U1
U1 is a major line of the Nuremberg U-Bahn rapid transit system, connecting key districts across the Nuremberg metropolitan area.
-
E.
U6
U6 is a major north–south line of the Berlin U-Bahn rapid transit system, connecting several key districts across the city.
- 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_69c008f873a481909b4d9f7e2db3c37d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f73cc8c8190a92a839c1ca804c7 |
completed | March 22, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c027f2e98c8190880752c9ae8aba4f |
completed | March 22, 2026, 5:33 p.m. |
Created at: March 22, 2026, 3:34 p.m.