Triple
T13856137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevaleret |
E333068
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Seine |
E6962
|
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: Seine | Statement: [Chevaleret, locatedNear, Seine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seine Context triple: [Chevaleret, locatedNear, Seine]
-
A.
Amper River
The Amper River is a Bavarian river that flows through Upper Bavaria, including the district of Freising, before joining the Isar River.
-
B.
Rhine
The Rhine is one of Europe's most important rivers, historically serving as a vital trade route and cultural boundary from the Alps through Germany to the North Sea.
-
C.
River Seine
chosen
The River Seine is a major waterway in northern France that flows through the heart of Paris and is central to the city's history, culture, and landscape.
-
D.
Eure River
The Eure River is a tributary of the Seine in northern France that flows through the city of Chartres and several other towns in the Normandy and Centre-Val de Loire regions.
-
E.
Meuse
Meuse is a department in northeastern France known for its rural landscapes and significant World War I battlefields, including Verdun.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02dc9f488190b7181dcb7e304632 |
completed | April 14, 2026, 9:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb648146c8190842a3da4e4c0e217 |
completed | May 7, 2026, 3:56 p.m. |
Created at: April 9, 2026, 10:14 p.m.