Triple
T2051898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gagauz |
E45586
|
entity |
| Predicate | culturalInfluences |
P14191
|
FINISHED |
| Object | Turkic |
—
|
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: Turkic | Statement: [Gagauz, culturalInfluences, Turkic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culturalInfluences Context triple: [Gagauz, culturalInfluences, Turkic]
-
A.
hasCulturalImpact
Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
-
B.
culturalInteraction
Indicates interactions or exchanges between entities that involve cultural practices, values, expressions, or influences.
-
C.
culturalSphere
chosen
Indicates that one entity belongs to, is influenced by, or participates in the cultural domain, tradition, or milieu defined by another entity.
-
D.
culturalCategory
Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
-
E.
regionOfCulturalImpact
Indicates the geographic area where an entity’s cultural influence, activities, or effects are most significantly felt or observed.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb99078d88190bc30fa4596f0bae8 |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7abba508190b872f345d3ba51bb |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:39 p.m.