Triple
T2233598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shabo language |
E49226
|
entity |
| Predicate | lexicalInfluenceHypothesis |
P23173
|
FINISHED |
| Object | influenced by Surmic 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: influenced by Surmic languages | Statement: [Shabo language, lexicalInfluenceHypothesis, influenced by Surmic languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lexicalInfluenceHypothesis Context triple: [Shabo language, lexicalInfluenceHypothesis, influenced by Surmic languages]
-
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.
languageInfluence
chosen
Indicates that one language has an effect on the development, usage, or characteristics of another language.
-
C.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
-
D.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
E.
linguisticRegister
Indicates the level of formality or stylistic variety in which a linguistic expression is typically used within a given context.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0913f1c8190ac9cfeb0f1c84a76 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.