Triple
T6724137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RER line E |
E153469
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Chelles–Gournay |
E751497
|
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: Chelles–Gournay | Statement: [RER line E, hasStation, Chelles–Gournay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chelles–Gournay Context triple: [RER line E, hasStation, Chelles–Gournay]
-
A.
Chelles–Gournay
chosen
Chelles–Gournay is a suburban railway station in the eastern Paris metropolitan area that serves as the outer terminus of RER line E.
-
B.
Crosne
Crosne is a small suburban commune in the Île-de-France region of northern France, located southeast of Paris.
-
C.
Gonesse
Gonesse is a commune in the northeastern suburbs of Paris, France, known historically as a rural town and now as part of the greater Paris metropolitan area.
-
D.
Vaucresson
Vaucresson is a suburban commune in the western outskirts of Paris, France, known for its residential character and green surroundings.
-
E.
Bourgueil
Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d13b296c8190bf54009063032c6d |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51147c4c8190b3c893700f48fc54 |
completed | April 3, 2026, 5:33 a.m. |
Created at: March 27, 2026, 2:08 p.m.