Triple
T28536829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiac French |
E722184
|
entity |
| Predicate | usesCodeSwitchingWith |
P178791
|
FINISHED |
| Object | English |
—
|
NE NERFINISHED |
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: [Chiac French, usesCodeSwitchingWith, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCodeSwitchingWith Context triple: [Chiac French, usesCodeSwitchingWith, English]
-
A.
codeSwitchedTo
Indicates that an entity has changed from using one language or code system to another within a given context or interaction.
-
B.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
C.
usesLanguageAs
Indicates that one entity communicates or operates using another entity as its language or linguistic medium.
-
D.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
E.
usesNonLinearLanguage
Indicates that the subject communicates or expresses ideas using non-linear, non-sequential, or otherwise non-traditionally structured language.
- F. None of above. chosen
Provenance (4 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_69f01a5d7ec88190ada2d5be7c06c35d |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71421e8d08190807ccfb15d0f0ddb |
completed | May 3, 2026, 9:23 a.m. |
Created at: April 28, 2026, 3:32 a.m.