Triple
T1197069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryukyuan languages |
E25690
|
entity |
| Predicate | hasLexicalRelation |
P11829
|
FINISHED |
| Object | shares cognates with Japanese |
—
|
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: shares cognates with Japanese | Statement: [Ryukyuan languages, hasLexicalRelation, shares cognates with Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLexicalRelation Context triple: [Ryukyuan languages, hasLexicalRelation, shares cognates with Japanese]
-
A.
hasLexicalInfluenceOn
Indicates that one linguistic element (such as a word, phrase, or lexicon) has affected or shaped the form, usage, or meaning of another linguistic element.
-
B.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
C.
hasLexicalSimilarityWith
chosen
Indicates that two linguistic items share a significant degree of similarity in form, structure, or wording.
-
D.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
E.
hasGrammaticalSimilarityTo
Indicates that two linguistic elements share similar grammatical structure, form, or function.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9a305c819091513394f1b67784 |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5d40a08190b7682d8ef8075421 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.