Triple
T8320735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ors |
E194825
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Sambre River |
E166937
|
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: Sambre River | Statement: [Ors, hasRiver, Sambre River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sambre River Context triple: [Ors, hasRiver, Sambre River]
-
A.
Sambre
chosen
The Sambre is a major river in northern France and southern Belgium that flows through the Walloon region before joining the Meuse at Namur.
-
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.
Meuse
Meuse is a department in northeastern France known for its rural landscapes and significant World War I battlefields, including Verdun.
-
D.
River Zenne
The River Zenne is a small Belgian river that flows through Brussels and surrounding towns, historically shaping the region’s development and urban landscape.
-
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_69ca82e7a8a88190a32bb5cc0feb012d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f67aee88190b245f8d6e57a40b2 |
completed | March 31, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce0278b9a88190a57a6b1b31c39ee8 |
completed | April 2, 2026, 5:45 a.m. |
Created at: March 30, 2026, 5:55 p.m.