Triple
T24470092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slovene alphabet |
E617073
|
entity |
| Predicate | digitalEncoding |
P5799
|
FINISHED |
| Object |
Windows-1250
Windows-1250 is a character encoding developed by Microsoft for Central and Eastern European languages that use Latin scripts, such as Polish, Czech, Slovak, and Slovene.
|
E1636180
|
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: Windows-1250 | Statement: [Slovene alphabet, digitalEncoding, Windows-1250]
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: Windows-1250 Triple: [Slovene alphabet, digitalEncoding, Windows-1250]
Generated description
Windows-1250 is a character encoding developed by Microsoft for Central and Eastern European languages that use Latin scripts, such as Polish, Czech, Slovak, and Slovene.
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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f299432b2881909502f9cbc7e4dbb0 |
completed | April 29, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0fe3922e708190abd9672b0f47bfef |
completed | May 22, 2026, 5:03 a.m. |
| NEDg | Description generation | batch_6a0fe6c7cf0c8190a519141e2d729f8a |
completed | May 22, 2026, 5:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0fe76385488190991e3bd99cd9d9e9 |
completed | May 22, 2026, 5:19 a.m. |
Created at: April 18, 2026, 2:20 a.m.