Triple
T2875091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romans-sur-Isère |
E56858
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object |
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.
|
E310981
|
NE FINISHED |
How this triple was built (4 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: Velenje | Statement: [Romans-sur-Isère, twinnedWith, Velenje]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Velenje Context triple: [Romans-sur-Isère, twinnedWith, Velenje]
-
A.
Maribor
Maribor is Slovenia’s second-largest city, known for its historic old town, wine culture, and the world’s oldest grapevine.
-
B.
Sevnica
Sevnica is a small town in central Slovenia known as the childhood home of former U.S. First Lady Melania Trump.
-
C.
Kladno
Kladno is an industrial city in the Czech Republic known historically for coal mining and steel production.
-
D.
Ptuj
Ptuj is one of Slovenia’s oldest towns, renowned for its well-preserved medieval architecture and rich cultural heritage along the Drava River.
-
E.
Novo Mesto, Slovenia
Novo Mesto is a historic town in southeastern Slovenia known for its cultural heritage and picturesque setting on the Krka River.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Velenje Triple: [Romans-sur-Isère, twinnedWith, Velenje]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Velenje Target entity description: 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.
-
A.
Maribor
Maribor is Slovenia’s second-largest city, known for its historic old town, wine culture, and the world’s oldest grapevine.
-
B.
Sevnica
Sevnica is a small town in central Slovenia known as the childhood home of former U.S. First Lady Melania Trump.
-
C.
Kladno
Kladno is an industrial city in the Czech Republic known historically for coal mining and steel production.
-
D.
Ptuj
Ptuj is one of Slovenia’s oldest towns, renowned for its well-preserved medieval architecture and rich cultural heritage along the Drava River.
-
E.
Novo Mesto, Slovenia
Novo Mesto is a historic town in southeastern Slovenia known for its cultural heritage and picturesque setting on the Krka River.
- F. None of above. chosen
Provenance (5 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abe004a64481908f1897d9054a7368 |
completed | March 7, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b08648923c8190bd544177b825a494 |
completed | March 10, 2026, 8:59 p.m. |
| NEDg | Description generation | batch_69b0b3763b8481909483bbaab1af5d69 |
completed | March 11, 2026, 12:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0b40e41e08190afb710c400765d01 |
completed | March 11, 2026, 12:15 a.m. |
Created at: March 6, 2026, 10:03 p.m.