Triple
T7438125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charleville-Mézières |
E171671
|
entity |
| Predicate | hasRailConnectionTo |
P848
|
FINISHED |
| Object | Reims |
E9677
|
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: Reims | Statement: [Charleville-Mézières, hasRailConnectionTo, Reims]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reims Context triple: [Charleville-Mézières, hasRailConnectionTo, Reims]
-
A.
Reims
chosen
Reims is a historic city in northeastern France known for its Gothic cathedral, role in French coronations, and significance during both World Wars.
-
B.
Troyes
Troyes is a historic city in northeastern France, known for its well-preserved medieval old town, half-timbered houses, and Gothic churches.
-
C.
Creil
Creil is a commuter town in northern France’s Oise department, known as a regional rail hub connecting Paris with Picardy via major train and RER lines.
-
D.
Meaux
Meaux is a historic commune in the Île-de-France region of north-central France, known for its cathedral, World War I heritage, and production of Brie de Meaux cheese.
-
E.
Amiens
Amiens is a historic city in northern France, known for its Gothic cathedral and role as the site of the 1802 Treaty of Amiens.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9abd319048190a24be5112c810489 |
completed | March 29, 2026, 10:46 p.m. |
Created at: March 27, 2026, 3:13 p.m.