Triple
T9219036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Cherbourg railway |
E221312
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Bernay |
E234308
|
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: Bernay | Statement: [Paris–Cherbourg railway, passesThrough, Bernay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernay Context triple: [Paris–Cherbourg railway, passesThrough, Bernay]
-
A.
Bernay
chosen
Bernay is a historic market town in the Normandy region of northern France, known for its medieval architecture and traditional Norman character.
-
B.
Fleurissant
Fleurissant was the early French colonial settlement that later developed into the modern city of Florissant, Missouri.
-
C.
Lancy
Lancy is a suburban municipality in western Switzerland that forms part of the urban area of Geneva.
-
D.
Besançon
Besançon is a historic city in eastern France, known for its well-preserved Vauban fortifications, rich cultural heritage, and role as a regional administrative and educational center.
-
E.
Vandoeuvres
Vandoeuvres is a small, affluent residential municipality located near the city of Geneva in western Switzerland.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda730f688190b64b2cc8c4898ac3 |
completed | April 1, 2026, 8:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d100b8f80c8190bef93de787227a51 |
completed | April 4, 2026, 12:14 p.m. |
Created at: March 30, 2026, 7:27 p.m.