Triple
T24598625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanuatu sand drawings |
E608751
|
entity |
| Predicate | languageAspect |
P6520
|
FINISHED |
| Object | visual language |
—
|
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: visual language | Statement: [Vanuatu sand drawings, languageAspect, visual language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAspect Context triple: [Vanuatu sand drawings, languageAspect, visual language]
-
A.
hasLanguageAspect
Indicates that an entity is associated with a particular linguistic aspect, such as tense, mood, or grammatical feature, in relation to a language.
-
B.
linguisticFeature
chosen
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
C.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
-
D.
languagePolicyAspect
Indicates an aspect or component of a broader language policy, such as its goals, rules, or implementation measures.
-
E.
languageSubject
Indicates that a particular language is the subject or topic being studied, discussed, or otherwise focused on in relation to another entity.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.