Triple
T3525928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drava |
E74537
|
entity |
| Predicate | flowsThroughCity |
P10456
|
FINISHED |
| Object | Ptuj |
E115510
|
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: Ptuj | Statement: [Drava, flowsThroughCity, Ptuj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ptuj Context triple: [Drava, flowsThroughCity, Ptuj]
-
A.
Ptuj
chosen
Ptuj is one of Slovenia’s oldest towns, renowned for its well-preserved medieval architecture and rich cultural heritage along the Drava River.
-
B.
Velenje
Velenje is a modern industrial town in northern Slovenia known for its coal mining heritage, large lakeside recreational area, and one of the largest Tito statues in the world.
-
C.
Kladno
Kladno is an industrial city in the Czech Republic known historically for coal mining and steel production.
-
D.
Sevnica
Sevnica is a small town in central Slovenia known as the childhood home of former U.S. First Lady Melania Trump.
-
E.
Dubnica nad Váhom
Dubnica nad Váhom is a town in western Slovakia known as an industrial center and the hometown of several notable Slovak athletes.
- 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6a8d0c819094d38b9c47fb67b4 |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bca41a88190b5550b9c1e763092 |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:19 p.m.