Triple
T5923499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TinyScheme |
E131749
|
entity |
| Predicate | typicalEmbeddingLanguage |
P42338
|
FINISHED |
| Object | C applications |
—
|
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: C applications | Statement: [TinyScheme, typicalEmbeddingLanguage, C applications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEmbeddingLanguage Context triple: [TinyScheme, typicalEmbeddingLanguage, C applications]
-
A.
typicalLanguages
chosen
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
B.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
-
C.
governingLanguage
Indicates the language that holds official or authoritative status over a given entity, such as a region, organization, or document.
-
D.
languageAssociation
Indicates an association or relationship between entities based on a language they use, represent, or are linked to.
-
E.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.