Triple
T15386495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PPDC Hong Kong Command |
E367928
|
entity |
| Predicate | languageInSetting |
P19095
|
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: [PPDC Hong Kong Command, languageInSetting, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageInSetting Context triple: [PPDC Hong Kong Command, languageInSetting, English]
-
A.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
B.
languageOfLocalization
Indicates the language into which something (such as software, content, or an interface) has been localized for use or display.
-
C.
navigationLanguage
Indicates the language used for navigation-related content, such as menus, directions, or interface controls.
-
D.
languageOfEnvironment
chosen
Indicates the language predominantly used or present in a given environment or context.
-
E.
currentLanguageSituation
Indicates the language currently being used or in effect in a given context or situation.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e74ff70819094c1a85f51d6e228 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.