Triple
T4769946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calvados |
E105902
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Eure |
E45086
|
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: Eure | Statement: [Calvados, borders, Eure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eure Context triple: [Calvados, borders, Eure]
-
A.
Eure
chosen
Eure is a river in northern France that flows through the regions of Normandy and Centre-Val de Loire before joining the Seine.
-
B.
Jever
Jever is a historic town in Lower Saxony, Germany, best known for its traditional North German architecture and the Jever Pilsener brewery.
-
C.
Geul
The Geul is a small river in the southeastern Netherlands and eastern Belgium, known for flowing through the hilly Limburg landscape and picturesque villages before joining the Meuse.
-
D.
Ems
Ems is a historic spa town in present-day Germany, renowned for its mineral springs and 19th-century status as a fashionable European resort.
-
E.
Ems
The Ems is a river in northwestern Germany that flows through several states before emptying into the North Sea.
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd655c9a2c8190adce3e2a8a1fa0a7 |
completed | March 20, 2026, 3:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a94e340819080fe92a2024abdaf |
completed | March 21, 2026, 6:28 a.m. |
Created at: March 20, 2026, 1:21 p.m.