Triple
T5336469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Västerhaninge station |
E123837
|
entity |
| Predicate | ticketSystem |
P25925
|
FINISHED |
| Object | SL Access |
E103979
|
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: SL Access | Statement: [Västerhaninge station, ticketSystem, SL Access]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SL Access Context triple: [Västerhaninge station, ticketSystem, SL Access]
-
A.
SL Access
chosen
SL Access is Stockholm's public transport smart card and ticketing system used for travel on buses, trains, and other SL services.
-
B.
Access
Access is Microsoft's desktop database management system that enables users to create, manage, and analyze relational databases through a graphical interface and integrated tools.
-
C.
Aceso
Aceso is a minor Greek goddess associated with the process of healing and the curing of illness.
-
D.
Ease of Access Center
Ease of Access Center is a Windows feature that centralizes accessibility settings and tools to help users with disabilities or special needs use their computers more easily.
-
E.
ACSES
ACSES (Advanced Civil Speed Enforcement System) is a positive train control technology used on U.S. railroads to enforce speed limits and signal compliance, enhancing operational safety.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85b104c081908b81236a0142e1c8 |
completed | March 20, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18c1e1f88190a47489a9491eaf08 |
completed | March 21, 2026, 10:16 p.m. |
Created at: March 20, 2026, 2 p.m.