Triple
T846398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lille |
E18284
|
entity |
| Predicate | railwayHubFor |
P14468
|
FINISHED |
| Object | Thalys |
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 | Statement: [Lille, railwayHubFor, Thalys]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thalys Context triple: [Lille, railwayHubFor, Thalys]
-
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.
Ouigo
Ouigo is a low-cost high-speed train service operated by France's SNCF, offering budget TGV travel with simplified onboard services.
-
D.
Intercités
Intercités is a network of French long-distance conventional trains operated by SNCF, connecting major cities and regions across the country.
-
E.
RegioExpress
RegioExpress is a category of Swiss regional express trains that provide relatively fast, limited-stop connections between major and medium-sized towns.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b66c908190a52f731119b77a1e |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c016a8a88190965e7c703b0329fb |
completed | March 4, 2026, 5:16 a.m. |
Created at: March 1, 2026, 7:38 p.m.