Triple
T294397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gare du Nord |
E6061
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | SNCF |
E37919
|
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: SNCF | Statement: [Gare du Nord, operator, SNCF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SNCF Context triple: [Gare du Nord, operator, SNCF]
-
A.
SNCF
chosen
SNCF is France’s national state-owned railway company, responsible for operating the country’s passenger and freight rail services and much of its rail infrastructure.
-
B.
Transilien
Transilien is the suburban and regional rail network operated by SNCF that serves the Île-de-France (Greater Paris) area.
-
C.
RATP group
RATP Group is a major French public transport operator that manages much of the Paris metro, tram, and bus networks and provides transit services internationally.
-
D.
TGV high-speed rail
TGV high-speed rail is France’s flagship high-speed train service that connects major cities and hubs, including direct links from Charles de Gaulle Airport to destinations across the country and into neighboring nations.
-
E.
RER C
RER C is a major line of the Paris regional express rail network that connects central Paris with several suburbs and key destinations, including access to Orly Airport.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e978420881908488df342a7d5e90 |
completed | Feb. 28, 2026, 1:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3a88778b48190856af2e89d21621a |
completed | March 1, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 1:06 p.m.