Triple
T502602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern France |
E10430
|
entity |
| Predicate | containsRiver |
P165
|
FINISHED |
| Object | Moselle |
E66813
|
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: Moselle | Statement: [Eastern France, containsRiver, Moselle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moselle Context triple: [Eastern France, containsRiver, Moselle]
-
A.
Moselle River
chosen
The Moselle River is a major European waterway flowing through France, Luxembourg, and Germany, renowned for its scenic valleys and wine-producing regions.
-
B.
Meuse
The Meuse is a major European river flowing through France, Belgium, and the Netherlands, historically important for transport, trade, and the development of surrounding regions.
-
C.
Marne
The Marne is a major river in northeastern France that flows through the Île-de-France region before joining the Seine near Paris.
-
D.
Nièvre
Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
-
E.
Semois River
The Semois River is a picturesque waterway in southern Belgium and northern France, known for winding through the rugged, forested landscapes of the Ardennes.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1339748819089f89691a1698dd9 |
completed | Feb. 28, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4ff465c2c819083d63547a4d0572a |
completed | March 2, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.