Triple
T525432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RER B line |
E10905
|
entity |
| Predicate | ownedBy |
P347
|
FINISHED |
| Object | Île-de-France Mobilités |
E44780
|
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: Île-de-France Mobilités | Statement: [RER B line, ownedBy, Île-de-France Mobilités]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Île-de-France Mobilités Context triple: [RER B line, ownedBy, Île-de-France Mobilités]
-
A.
Île-de-France Mobilités
chosen
Île-de-France Mobilités is the public agency responsible for organizing, coordinating, and funding public transportation services across the Paris metropolitan region.
-
B.
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.
-
C.
Transilien
Transilien is the suburban and regional rail network operated by SNCF that serves the Île-de-France (Greater Paris) area.
-
D.
SNCF
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.
-
E.
RER A
RER A is one of the main lines of the Paris regional express network, carrying large volumes of commuters and travelers between central Paris and its suburbs.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b7f448819087e5e7f3b37d7142 |
completed | Feb. 28, 2026, 1:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4c66d76588190864ac6a992c44545 |
completed | March 1, 2026, 11:06 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.