Triple
T23396477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitsai language |
E559371
|
entity |
| Predicate | hasDescendantLanguage |
P89065
|
FINISHED |
| Object | none (no known daughter 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: none (no known daughter languages) | Statement: [Kitsai language, hasDescendantLanguage, none (no known daughter languages)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDescendantLanguage Context triple: [Kitsai language, hasDescendantLanguage, none (no known daughter languages)]
-
A.
hasSubLanguage
Indicates that one language is a subset, variant, or specialized form of another language.
-
B.
hasSuccessorLanguageInRegion
Indicates that one language is followed or replaced by another language within a specific geographic region.
-
C.
hasPrimaryLanguageSubbranch
Indicates that one language subbranch is the main or principal subbranch associated with a given language or language family.
-
D.
hasRelatedLanguage
Indicates that one language is related to another through shared linguistic origins, features, or classification.
-
E.
linguisticDescendant
chosen
Indicates that one language is historically derived from, or has evolved out 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_69e24549610c8190a069d6411ce5f661 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a4dc48008190bdcf92f8d9a5232d |
completed | April 29, 2026, 6:27 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:36 p.m.