Triple
T15980896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RTC buses |
E387566
|
entity |
| Predicate | secondaryLanguageOfInformation |
P9103
|
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: [RTC buses, secondaryLanguageOfInformation, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryLanguageOfInformation Context triple: [RTC buses, secondaryLanguageOfInformation, English]
-
A.
secondaryLanguageContext
Indicates that the associated information, interaction, or content occurs within or is tailored to a secondary (non-primary) language setting or usage context.
-
B.
laterSecondaryLanguageOfAdministration
Indicates that one language served as a subsequent or later secondary language used for administrative purposes in relation to another language.
-
C.
primaryLanguageSide2
Indicates that the second entity in the relationship uses or is associated with the primary language specified.
-
D.
hasSecondaryLanguage
chosen
Indicates that an entity possesses or uses a secondary language in addition to its primary language.
-
E.
hasSecondaryNationalLanguage
Indicates that an entity possesses an officially recognized secondary national language in addition to its primary national 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.