Triple
T32815064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin-Lankwitz station |
E839262
|
entity |
| Predicate | isElectrifiedFor |
P59679
|
FINISHED |
| Object | Berlin S-Bahn trains |
—
|
NE NERFINISHED |
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: Berlin S-Bahn trains | Statement: [Berlin-Lankwitz station, isElectrifiedFor, Berlin S-Bahn trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isElectrifiedFor Context triple: [Berlin-Lankwitz station, isElectrifiedFor, Berlin S-Bahn trains]
-
A.
isElectrifiedSince
Indicates that an entity has had electrical power or electrification continuously from a specified point in time onward.
-
B.
isElectrifiedSectionOf
Indicates that one section or segment is a part of a larger entity and has been equipped with electrical power or electrification.
-
C.
hasElectrificationStatus
chosen
Indicates that an entity possesses a specified type or level of electrification (e.g., electrified, non-electrified, partially electrified).
-
D.
isElectricRailway
Indicates that a given railway system operates using electric power rather than diesel or other forms of propulsion.
-
E.
isElectrically
Indicates that one entity has an electrical property, connection, or interaction in relation to another entity.
- F. None of above.
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_69f3493df9008190a8f5d843dcd77704 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6ce6d659881909ddcec1d2966e020 |
completed | May 3, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:15 a.m.