Triple
T8300387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wikimedia unified login |
E194335
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Wikiversity |
E37906
|
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: Wikiversity | Statement: [Wikimedia unified login, usedBy, Wikiversity]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wikiversity Context triple: [Wikimedia unified login, usedBy, Wikiversity]
-
A.
Wikiversity
chosen
Wikiversity is a Wikimedia Foundation project that provides a free, collaborative platform for creating and using educational resources and learning materials.
-
B.
Wikibooks
Wikibooks is a Wikimedia Foundation project that hosts collaboratively written, free-content textbooks and instructional guides.
-
C.
Ukrainian Wikiversity
Ukrainian Wikiversity is the Ukrainian-language edition of Wikiversity, a Wikimedia Foundation project focused on creating and sharing free educational resources and learning materials.
-
D.
Citizendium
Citizendium is an expert-guided, wiki-based online encyclopedia project founded as an alternative to Wikipedia, emphasizing real-name authorship and expert oversight.
-
E.
Curriki
Curriki is an education-focused nonprofit organization that provides free, open-source digital learning resources and tools for teachers and students worldwide.
- 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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7e879c588190a6f95cf7795541ad |
completed | March 31, 2026, 7:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd953b5fd881909696eb2647dc5f92 |
completed | April 1, 2026, 9:59 p.m. |
Created at: March 30, 2026, 5:53 p.m.