Triple
T5840693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trikken i Oslo |
E129584
|
entity |
| Predicate | hasRollingStockType |
P1305
|
FINISHED |
| Object | SL79 tram |
E129582
|
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: SL79 tram | Statement: [Trikken i Oslo, hasRollingStockType, SL79 tram]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SL79 tram Context triple: [Trikken i Oslo, hasRollingStockType, SL79 tram]
-
A.
SL79 tram
chosen
The SL79 tram is a class of articulated light rail vehicles used for passenger service on the Oslo Tramway network in Norway.
-
B.
SL95 tram
The SL95 tram is a high-floor, bi-directional tram model used in Oslo, Norway, known for its large capacity and operation on the city’s light rail and tram network.
-
C.
LM-93 tram
The LM-93 tram is a Russian-built light rail vehicle model commonly used in city tram and metrotram systems such as the Volgograd Metrotram.
-
D.
T-68 tram
The T-68 tram was a type of light rail vehicle used on Greater Manchester’s Metrolink system in the UK before being replaced by newer models.
-
E.
Stadler Tango trams
Stadler Tango trams are modern, low-floor light rail vehicles built by Stadler Rail, commonly used in European cities for high-capacity, urban public transport services.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034d6f09c81908dfb3c2c51a2f5a9 |
completed | March 22, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0bfce88f88190bbc78ce9c7c3c107 |
completed | March 23, 2026, 4:21 a.m. |
Created at: March 22, 2026, 3:54 p.m.