Triple
T10574936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodalies de Catalunya |
E249583
|
entity |
| Predicate | hasService |
P182
|
FINISHED |
| Object | R2 |
E599013
|
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: R2 | Statement: [Rodalies de Catalunya, hasService, R2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R2 Context triple: [Rodalies de Catalunya, hasService, R2]
-
A.
R2
R2 is the MBTA station code used to identify Ashmont station on Boston's Red Line transit system.
-
B.
R2 Nord
R2 Nord is a commuter rail service line that operates in the northern sector of its regional rail network, connecting suburban areas with major urban centers.
-
C.
R2N
chosen
R2N is the symbol used to designate the R2 Nord commuter rail line in the Barcelona suburban railway network.
-
D.
R2000
The R2000 is a 32-bit MIPS RISC microprocessor that became one of the earliest and most influential commercial implementations of the MIPS architecture in the mid-1980s.
-
E.
R27
R27 is the internal station code used by the New York City Subway for the Broad Street station on the BMT Nassau Street Line.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52749dda08190b0c9627a931c5848 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b5d89748190bb398943e4a16e9b |
completed | April 10, 2026, 7:11 p.m. |
Created at: April 6, 2026, 12:38 p.m.