Triple
T19991375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Styria |
E494071
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Mura |
—
|
NE NERFINISHED |
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: Mura | Statement: [Lower Styria, hasRiver, Mura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mura Context triple: [Lower Styria, hasRiver, Mura]
-
A.
Mura
Mura is a small historic village in the Bages comarca of Catalonia, Spain, known for its well-preserved medieval architecture and scenic natural surroundings.
-
B.
Mura
chosen
The Mura is a Central European river that flows through Austria, Slovenia, and Croatia before joining the Drava River.
-
C.
Murau
Murau is a historic small town in the Austrian Alps known for its medieval architecture, timber industry, and popular nearby ski and hiking areas.
-
D.
Goura
Goura is a small village in the Peloponnese region of Greece, known for its traditional stone architecture and mountainous surroundings.
-
E.
Moriya
Moriya is a city in Ibaraki Prefecture, Japan, known as a suburban residential and commuter hub within the Greater Tokyo area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe00b908190bda6b9a3a3281ec0 |
completed | April 20, 2026, 5:18 p.m. |
Created at: April 11, 2026, 3:31 p.m.