Triple
T8005427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stade de Reims |
E186352
|
entity |
| Predicate | basedIn |
P40
|
FINISHED |
| Object | Reims, France |
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, France | Statement: [Stade de Reims, basedIn, Reims, France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reims, France Context triple: [Stade de Reims, basedIn, Reims, France]
-
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.
Étaples, France
Étaples, France is a coastal town in northern France’s Pas-de-Calais department, historically known as a fishing port and for its role in World War I as the site of a major British military base and cemetery.
-
C.
Bezons, France
Bezons, France is a suburban commune in the northwestern outskirts of Paris known for hosting major corporate offices and technology companies.
-
D.
Ermont, France
Ermont is a suburban commune in the northern outskirts of Paris, France, known for its residential character and transport links within the Val-d'Oise department.
-
E.
Amiens, France
Amiens, France is a historic city in northern France known for its Gothic cathedral and as the birthplace of French President Emmanuel Macron.
- 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3cf72fc08190aa78b97c1ab92f90 |
completed | March 31, 2026, 3:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe127afe0819092d5ad0c430fadc4 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:18 p.m.