Triple
T7308532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borgeet |
E168035
|
entity |
| Predicate | inLanguageVariant |
P34737
|
FINISHED |
| Object | early Assamese (old Assamese) |
—
|
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: early Assamese (old Assamese) | Statement: [Borgeet, inLanguageVariant, early Assamese (old Assamese)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inLanguageVariant Context triple: [Borgeet, inLanguageVariant, early Assamese (old Assamese)]
-
A.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
B.
linguisticVariant
chosen
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
C.
languageOfVariant
Indicates that one entity is the language in which a particular variant or version of another entity is expressed.
-
D.
usesLocalLanguageVariant
Indicates that an entity employs a region-specific or localized form of a language rather than a standard or global variant.
-
E.
hasRegionalVariationsIn
Indicates that something exhibits different forms, versions, or characteristics depending on the geographic region.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebda7b748190a230a22ecea79342 |
completed | March 27, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69c6e7705f4881909793071dee50c557 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:01 p.m.