Triple
T19311867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laos and Vietnam |
E482990
|
entity |
| Predicate | shareLinguisticInfluences |
P61006
|
FINISHED |
| Object | Pali-Sanskrit |
—
|
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: Pali-Sanskrit | Statement: [Laos and Vietnam, shareLinguisticInfluences, Pali-Sanskrit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareLinguisticInfluences Context triple: [Laos and Vietnam, shareLinguisticInfluences, Pali-Sanskrit]
-
A.
shareLanguageInfluence
chosen
Indicates that two entities affect or shape each other’s language use, development, or characteristics through mutual or shared influence.
-
B.
languageInfluence
Indicates that one language has an effect on the development, usage, or characteristics of another language.
-
C.
linguisticInfluence
Indicates that one entity has affected, shaped, or contributed to the language, style, or linguistic features of another entity.
-
D.
influencesLanguageOf
Indicates that one entity affects, shapes, or alters the language used by another entity.
-
E.
languageOfInfluence
Indicates a relationship where one language has influenced the development, usage, or characteristics 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604ce5de081909811c49f56ba94bb |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:32 p.m.