Triple
T3488864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Laloux |
E73676
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Gare de Tours |
E282840
|
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 Tours | Statement: [Victor Laloux, notableWork, Gare de Tours]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gare de Tours Context triple: [Victor Laloux, notableWork, Gare de Tours]
-
A.
Gare de Tours
chosen
Gare de Tours is the main railway station serving the city of Tours in central France, acting as a regional and intercity transport hub.
-
B.
Paris-Saint-Lazare station
Paris-Saint-Lazare station is one of the main railway termini in Paris, serving as a major hub for suburban and regional trains in the western part of the Île-de-France region.
-
C.
Gare de Nantes
Gare de Nantes is the main railway station serving the city of Nantes in western France, providing regional and high-speed train connections.
-
D.
Reims station
Reims station is the main railway station serving the city of Reims in northeastern France, providing regional and high-speed train connections.
-
E.
Gare de Lyon
Gare de Lyon is one of Paris’s major railway terminals, serving high-speed and regional trains to southeastern France and international destinations.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbb92b3ac8190b8675f5a5e9d4408 |
completed | March 8, 2026, 6:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5db5d2fcc8190818b79d873cebcf6 |
completed | March 14, 2026, 10:04 p.m. |
Created at: March 8, 2026, 3:18 p.m.