Triple
T3599624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champ |
E76222
|
entity |
| Predicate | languageOfAudience |
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: [Champ, languageOfAudience, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfAudience Context triple: [Champ, languageOfAudience, English]
-
A.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
B.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
C.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
D.
languageOfCoverage
Indicates the language in which the coverage, such as reporting or documentation about something, is expressed.
-
E.
dominantMediaLanguage
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc19fd57481908ce5c9daf168e213 |
completed | March 8, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69adb83b66708190bb9d2f23d6fd308e |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.