Triple
T22557865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EC |
E557734
|
entity |
| Predicate | standsFor |
P590
|
FINISHED |
| Object | EuroCity |
—
|
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: EuroCity | Statement: [EC, standsFor, EuroCity]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EuroCity Context triple: [EC, standsFor, EuroCity]
-
A.
EuroCity trains
chosen
EuroCity trains are a network of high-quality international express passenger services that connect major cities across European countries with fast, comfortable, and cross-border rail travel.
-
B.
InterCityExpress
InterCityExpress is Germany’s high-speed train service operated by Deutsche Bahn, known for fast long-distance connections between major cities and neighboring countries.
-
C.
Thalys
Thalys is a high-speed international train service connecting major cities in France, Belgium, the Netherlands, and Germany.
-
D.
TGV Lyria
TGV Lyria is a high-speed train service linking France and Switzerland, operated as a joint venture between SNCF and Swiss Federal Railways.
-
E.
Intercity Express Train
The Intercity Express Train is a modern high-speed passenger train used on long-distance routes in the UK, known for faster journeys, improved comfort, and greater energy efficiency compared to older rolling stock.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f7b06e08190b3ca82a783965942 |
completed | April 29, 2026, 1:31 a.m. |
Created at: April 16, 2026, 8:52 p.m.