Triple
T3848859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin-Schöneberg station |
E85239
|
entity |
| Predicate | connectsWithMode |
P51916
|
FINISHED |
| Object | regional rail |
—
|
LITERAL 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: regional rail | Statement: [Berlin-Schöneberg station, connectsWithMode, regional rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsWithMode Context triple: [Berlin-Schöneberg station, connectsWithMode, regional rail]
-
A.
connectsWithin
Indicates that one entity establishes a connection or link between elements that lie inside the bounds or scope of another entity.
-
B.
connectionTo
Indicates a relationship in which one entity is linked, associated, or otherwise related to another entity.
-
C.
connectionEstablishmentMethod
Indicates the method or mechanism by which a connection between entities is initiated or established.
-
D.
connectsState
Indicates a relationship where one entity serves as a link or conduit between different states, conditions, or statuses of another entity.
-
E.
connectsUnder
Indicates that one entity forms a connection to another entity by passing beneath or under it.
- F. None of above. chosen
Provenance (4 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcde86081908cf3840ae002acfa |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee8d9b328819080158be59e5bcc97 |
completed | March 9, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:19 p.m.