Triple
T20153019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RubberNinja |
E491483
|
entity |
| Predicate | channelLanguage |
P18209
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [RubberNinja, channelLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: channelLanguage Context triple: [RubberNinja, channelLanguage, English]
-
A.
languageDiscussedIn
Indicates that a particular language is the topic of discussion within a specified context, source, or discourse.
-
B.
languageBarrierWith
Indicates that communication between the two entities is hindered or obstructed due to differences in language.
-
C.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
-
D.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
E.
navigationLanguage
Indicates the language used for navigation-related content, such as menus, directions, or interface controls.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667dda9b4819097ff66bb2b50fc21 |
completed | April 20, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69e54cfd924881909b55f3e4d3e7e070 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:34 p.m.