Triple
T16184629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burúśaski |
E392767
|
entity |
| Predicate | hasNominalClassSystem |
P5217
|
FINISHED |
| Object | four-gender system |
—
|
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: four-gender system | Statement: [Burúśaski, hasNominalClassSystem, four-gender system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNominalClassSystem Context triple: [Burúśaski, hasNominalClassSystem, four-gender system]
-
A.
hasNounClassSystem
chosen
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
-
B.
hasNominalMorphology
Indicates that an entity possesses a system of nominal morphology, such as inflectional or derivational markers on nouns.
-
C.
hasNounClassCount
Indicates the number of distinct noun classes that are associated with or defined for a given entity.
-
D.
hasNounSystemFrom
Indicates that something possesses or is associated with a noun-based system that originates from or is derived from a specified source.
-
E.
hasPronounSystem
Indicates that an entity possesses or employs a particular system or set of rules for using pronouns.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205fc080819097858f36253fef7c |
completed | April 17, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.