Triple
T23411542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinglish |
E560080
|
entity |
| Predicate | originalLanguageMix |
P75592
|
FINISHED |
| Object | English and Mandarin dialogue |
—
|
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 and Mandarin dialogue | Statement: [Chinglish, originalLanguageMix, English and Mandarin dialogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLanguageMix Context triple: [Chinglish, originalLanguageMix, English and Mandarin dialogue]
-
A.
languageMix
chosen
Indicates that multiple languages are used together or intermixed within the same context, communication, or content.
-
B.
originalLanguageStatus
Indicates the status or condition of something with respect to its original language (e.g., whether it is in, derived from, or altered from the language in which it was first created).
-
C.
originalLanguageContext
Indicates the language in which something was first created or expressed, providing the original linguistic context for its content or meaning.
-
D.
originalLanguageSupport
Indicates that one entity provides or maintains functionality, content, or interaction in the original language of another entity.
-
E.
originalLanguageText
Indicates that a text is expressed in its original, untranslated language.
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a51183bc8190bd4860607b26b4b2 |
completed | April 29, 2026, 6:28 a.m. |
| PD | Predicate disambiguation | batch_69f061ed34288190a2e5e8cae03b0095 |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:38 p.m.