Triple
T19826671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ermont–Valmondois line |
E476342
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Taverny station |
—
|
NE NERFINISHED |
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: Taverny station | Statement: [Ermont–Valmondois line, hasStation, Taverny station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taverny station Context triple: [Ermont–Valmondois line, hasStation, Taverny station]
-
A.
Taverny station
chosen
Taverny station is a suburban railway stop in the Val-d'Oise department of northern France that serves the commune of Taverny on the Transilien network from Paris.
-
B.
Beaulieu station
Beaulieu station is a Brussels Metro station on the eastern section of the network serving the Auderghem municipality.
-
C.
Courchavon railway station
Courchavon railway station is a small regional train stop in the municipality of Courchavon in the Swiss canton of Jura.
-
D.
Tribunales station
Tribunales station is a Buenos Aires Underground stop on Line D located near the city’s main judicial district and courthouse complex.
-
E.
Villiers station
Villiers station is a Paris Métro station in the 8th and 17th arrondissements, serving as an interchange between lines 2 and 3.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656cb20788190b9deac6b8af6a55d |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.