Triple
T314191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loukko manor, Askainen, Grand Duchy of Finland |
E7670
|
entity |
| Predicate | hasLanguageEnvironment |
P9278
|
FINISHED |
| Object | Finnish |
—
|
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: Finnish | Statement: [Loukko manor, Askainen, Grand Duchy of Finland, hasLanguageEnvironment, Finnish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageEnvironment Context triple: [Loukko manor, Askainen, Grand Duchy of Finland, hasLanguageEnvironment, Finnish]
-
A.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
B.
hasLanguageOn
chosen
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
C.
hasProtoLanguage
Indicates that a language or language family originates from, or is derived from, a specified proto-language.
-
D.
hasLanguageGroup
Indicates that an entity belongs to, is associated with, or is categorized under a particular language group.
-
E.
hasLanguageModel
Indicates that an entity possesses, uses, or is associated with a particular language model.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea62f830819089e94b3aa3e4e187 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e9428098819089d5950cd2c96dc4 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:07 p.m.