Triple
T11056307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Institution Narrative |
E261384
|
entity |
| Predicate | languageVariants |
P97547
|
FINISHED |
| Object | exists in many vernacular languages |
—
|
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: exists in many vernacular languages | Statement: [Institution Narrative, languageVariants, exists in many vernacular languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageVariants Context triple: [Institution Narrative, languageVariants, exists in many vernacular languages]
-
A.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
B.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
C.
brandLanguageVariant
Indicates that one language variant of a brand is related to or derived from another language version of the same brand.
-
D.
languageOfVariant
Indicates that one entity is the language in which a particular variant or version of another entity is expressed.
-
E.
languageBranch
Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a152b4819095b74a8996346077 |
completed | April 9, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69d7440da46c8190a77380d5d747ac9c |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750c99f9881908ee2b01b6ce4b3a1 |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:26 p.m.