Triple
T31157708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hopelandic |
E794256
|
entity |
| Predicate | languageStructure |
P199910
|
FINISHED |
| Object | nonsense syllables |
—
|
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: nonsense syllables | Statement: [Hopelandic, languageStructure, nonsense syllables]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageStructure Context triple: [Hopelandic, languageStructure, nonsense syllables]
-
A.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
-
B.
languageForm
Indicates the specific linguistic form or expression in which something is conveyed or represented.
-
C.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
languageSubject
Indicates that a particular language is the subject or topic being studied, discussed, or otherwise focused on in relation to another entity.
-
E.
languageDesigned
Indicates that one entity created or developed the language used or associated with another entity.
- 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_69f224d504908190b01278dcb7fc3fa7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff63e6b61081909c648bf0ff279481 |
completed | May 9, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ff6381867881908ae0545df4b71df5 |
completed | May 9, 2026, 4:40 p.m. |
| PDg | Predicate description generation | batch_69ff63e5c35081908f69ac44e12b8f52 |
completed | May 9, 2026, 4:42 p.m. |
Created at: April 29, 2026, 9:07 p.m.