Triple
T871363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GPT-3 |
E18819
|
entity |
| Predicate | trainingDataSource |
P21073
|
FINISHED |
| Object | Wikipedia |
E19879
|
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: Wikipedia | Statement: [GPT-3, trainingDataSource, Wikipedia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wikipedia Context triple: [GPT-3, trainingDataSource, Wikipedia]
-
A.
Wikipedia
chosen
Wikipedia is a free, collaboratively edited online encyclopedia that allows users worldwide to create and modify its articles.
-
B.
Wikia
Wikia is a for-profit, community-driven wiki hosting platform (now known as Fandom) that provides free tools for fans to create and manage collaborative encyclopedias on their favorite topics.
-
C.
Encyclopaedia Britannica
Encyclopaedia Britannica is a long-standing, highly respected general knowledge reference work first published in the 18th century and now available in both print and digital formats.
-
D.
Wikisource
Wikisource is a free online digital library of public domain and freely licensed texts that anyone can read and help transcribe.
-
E.
Wikiversity
Wikiversity is a Wikimedia Foundation project that provides a free, collaborative platform for creating and using educational resources and learning materials.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b8063081909566c404ca63a29e |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3cb9a648190981182add42325f3 |
completed | March 4, 2026, 3:15 a.m. |
Created at: March 1, 2026, 7:39 p.m.