Triple
T1736210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris public transport Zone 1 |
E37924
|
entity |
| Predicate | fareSystemUsedBy |
P395
|
FINISHED |
| Object | SNCF Transilien |
E37920
|
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 Transilien | Statement: [Paris public transport Zone 1, fareSystemUsedBy, SNCF Transilien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SNCF Transilien Context triple: [Paris public transport Zone 1, fareSystemUsedBy, SNCF Transilien]
-
A.
Transilien
chosen
Transilien is the suburban and regional rail network operated by SNCF that serves the Île-de-France (Greater Paris) area.
-
B.
SNCF Réseau
SNCF Réseau is the French state-owned rail infrastructure manager responsible for operating, maintaining, and developing France’s national railway network.
-
C.
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.
-
D.
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.
-
E.
RER network
The RER network is a rapid transit system of express suburban trains serving Paris and its surrounding metropolitan area, integrating both urban and regional rail services.
- 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_69abaffd9b68819084f6c4d5e1aace1e |
completed | March 7, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5c065088190b831c65ae55eed14 |
completed | March 8, 2026, 5:45 p.m. |
Created at: March 4, 2026, 7:30 p.m.