Triple
T8301925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamil Wikinews |
E194367
|
entity |
| Predicate | mainContentType |
P82617
|
FINISHED |
| Object | news articles |
—
|
LITERAL 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: news articles | Statement: [Tamil Wikinews, mainContentType, news articles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainContentType Context triple: [Tamil Wikinews, mainContentType, news articles]
-
A.
featuredContentType
Indicates the specific type or category of content that is highlighted or promoted as featured.
-
B.
secondaryContentType
Indicates the type or category of additional, non-primary content associated with an entity or resource.
-
C.
primaryContent
Indicates that one entity serves as the main or most important content associated with another entity.
-
D.
notableContentType
Indicates the type or category of content for which an entity is notable or best known.
-
E.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
- F. None of above. chosen
Provenance (4 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_69cb7e891030819097f4a26992a8b469 |
completed | March 31, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:53 p.m.