Triple
T1736171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XPG |
E37923
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Thalys services |
E38855
|
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: Thalys services | Statement: [XPG, associatedWith, Thalys services]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thalys services Context triple: [XPG, associatedWith, Thalys services]
-
A.
Thalys
chosen
Thalys is a high-speed international train service connecting major cities in France, Belgium, the Netherlands, and Germany.
-
B.
Eurostar
Eurostar is a high-speed international train service connecting the United Kingdom with mainland Europe via the Channel Tunnel, linking cities such as London, Paris, and Brussels.
-
C.
SNCB/NMBS
SNCB/NMBS is the Belgian national railway company responsible for operating most passenger train services and managing much of the rail infrastructure in Belgium.
-
D.
Intercités
Intercités is a network of French long-distance conventional trains operated by SNCF, connecting major cities and regions across the country.
-
E.
ProRail
ProRail is the Dutch government-owned company responsible for managing and maintaining the national railway infrastructure in the Netherlands.
- 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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63a369048190bae352573f5082f1 |
completed | March 6, 2026, 5:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8b008b7881909ac568af010bcf99 |
completed | March 8, 2026, 2:43 p.m. |
Created at: March 4, 2026, 7:30 p.m.