Triple
T9732565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Train Bleu |
E235979
|
entity |
| Predicate | hasView |
P854
|
FINISHED |
| Object | Gare de Lyon concourse |
E6964
|
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: Gare de Lyon concourse | Statement: [Le Train Bleu, hasView, Gare de Lyon concourse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gare de Lyon concourse Context triple: [Le Train Bleu, hasView, Gare de Lyon concourse]
-
A.
Gare de Lyon
chosen
Gare de Lyon is one of Paris’s major railway terminals, serving high-speed and regional trains to southeastern France and international destinations.
-
B.
Gare de l'Est
Gare de l'Est is one of Paris's major railway stations, serving eastern France and international destinations such as Germany and Luxembourg.
-
C.
Porte Saint-Lazare
Porte Saint-Lazare is one of the historic city gates integrated into the medieval fortifications of Avignon, France.
-
D.
Châtelet–Les Halles station
Châtelet–Les Halles station is one of Paris’s largest and busiest underground transport hubs, connecting multiple Métro and RER lines beneath the central Les Halles district.
-
E.
Gare Montparnasse
Gare Montparnasse is one of Paris’s major railway terminals, serving primarily southwestern France and known for its modern complex and historic 1895 train crash.
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9eb3d6e4819090b3c7fb92550c57 |
completed | April 1, 2026, 10:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d74fb63b7081909cb6faddd795ced6 |
completed | April 9, 2026, 7:05 a.m. |
Created at: March 30, 2026, 8:22 p.m.