Triple
T8300344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Help (Wikimedia Commons namespace) |
E194334
|
entity |
| Predicate | hasContentModel |
P70467
|
FINISHED |
| Object | wikitext |
—
|
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: wikitext | Statement: [Help (Wikimedia Commons namespace), hasContentModel, wikitext]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasContentModel Context triple: [Help (Wikimedia Commons namespace), hasContentModel, wikitext]
-
A.
supportsContentModels
chosen
Indicates that an entity provides compatibility with, or can operate using, specified content models.
-
B.
hasComponentModel
Indicates that an entity includes or is associated with a specific component model as part of its structure or configuration.
-
C.
hasContentFrom
Indicates that one entity’s content is derived from, includes, or is based on another entity.
-
D.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
E.
hasContentSummary
Indicates that an entity is associated with a brief descriptive summary of its content.
- F. None of above.
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. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:53 p.m.