Triple
T11457194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Le Havre railway |
E271559
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Le Havre station |
E756347
|
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: Le Havre station | Statement: [Paris–Le Havre railway, terminus, Le Havre station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Havre station Context triple: [Paris–Le Havre railway, terminus, Le Havre station]
-
A.
Gare du Havre
chosen
Gare du Havre is the main railway station in Le Havre, France, serving as a key regional and intercity transport hub.
-
B.
Havre station
Havre station is a historic Amtrak passenger rail station in Havre, Montana, serving as a key stop along the Empire Builder route across the northern United States.
-
C.
Reims station
Reims station is the main railway station serving the city of Reims in northeastern France, providing regional and high-speed train connections.
-
D.
Gare de Cherbourg
Gare de Cherbourg is a major railway station in Cherbourg-en-Cotentin, France, serving as a key regional and intercity rail terminus in Normandy.
-
E.
Gare de Caen
Gare de Caen is the main railway station serving the city of Caen in northwestern France, providing regional and long-distance train connections.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d81c71b1208190be1d5623d18e0222 |
completed | April 9, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6248d0db881909999049356f53ff6 |
completed | April 20, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:35 p.m.