Triple
T19247922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cambrai railway station |
E481311
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Busigny |
—
|
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: Busigny | Statement: [Cambrai railway station, connectsTo, Busigny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Busigny Context triple: [Cambrai railway station, connectsTo, Busigny]
-
A.
Busigny
chosen
Busigny is a small commune in the Nord department of northern France, situated within the Hauts-de-France region.
-
B.
Grigny
Grigny is a suburban commune in the southern outskirts of Paris, France, known for its large housing estates and diverse population.
-
C.
Élancourt
Élancourt is a suburban commune in the Yvelines department of the Île-de-France region in north-central France, known for its residential areas and proximity to Paris.
-
D.
Meyriez
Meyriez is a small municipality in the canton of Fribourg in western Switzerland, situated on the shores of Lake Murten.
-
E.
Charpennes
Charpennes is a prominent urban district in the Lyon metropolitan area, known for its major transport hub and dense residential and commercial activity.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb2e7cf881908dafd45d7a305c52 |
completed | April 20, 2026, 10:08 a.m. |
Created at: April 10, 2026, 1:27 p.m.