Triple
T29007633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black International |
E736477
|
entity |
| Predicate | notableLanguageOfActivity |
P203740
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Black International, notableLanguageOfActivity, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLanguageOfActivity Context triple: [Black International, notableLanguageOfActivity, German]
-
A.
notableLanguageOfWorks
Indicates that a particular language is especially prominent or significant among the works created by an entity.
-
B.
notableMemberLanguage
Indicates that the language is notably associated with or used by a prominent member of the referenced group or entity.
-
C.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
D.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
E.
notableLanguageOfEligiblePrograms
Indicates that the specified language is a significant or primary language used in the programs that qualify under certain eligibility criteria.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a01e27bb77c8190a7686b77a524f177 |
completed | May 11, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_6a01da2614788190b31db15539f5ba58 |
completed | May 11, 2026, 1:31 p.m. |
| PDg | Predicate description generation | batch_6a01e27af6488190af75efc2283d99b3 |
completed | May 11, 2026, 2:06 p.m. |
Created at: April 28, 2026, 9:39 a.m.