Triple
T8425244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bebot |
E198966
|
entity |
| Predicate | featuresCodeSwitching |
P70080
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Bebot, featuresCodeSwitching, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCodeSwitching Context triple: [Bebot, featuresCodeSwitching, yes]
-
A.
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.
-
B.
languageOfCode
Indicates that a programming code artifact is written in, or uses, a particular programming language.
-
C.
taalcode
Indicates the language code associated with an entity, specifying in which language something is expressed or encoded.
-
D.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
E.
hasSociolinguisticPhenomenon
chosen
Indicates a relationship where a subject exhibits, involves, or is associated with a particular sociolinguistic phenomenon (such as dialectal variation, code-switching, or language change in social context).
- 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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb85a2871081908a4093838fc93b5a |
completed | March 31, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69cb70d7ea348190aafbf8ca02b7b7d5 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:07 p.m.