Triple
T30279028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latvia–Estonia border |
E770033
|
entity |
| Predicate | separatesLanguages |
P76456
|
FINISHED |
| Object | Latvian |
—
|
NE NERFINISHED |
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: Latvian | Statement: [Latvia–Estonia border, separatesLanguages, Latvian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: separatesLanguages Context triple: [Latvia–Estonia border, separatesLanguages, Latvian]
-
A.
separatesLinguisticRegions
chosen
Indicates that one entity serves as a boundary or divider between distinct linguistic regions or language areas.
-
B.
mainLinguisticCleavage
Indicates the primary division or contrast within a linguistic system or community, such as a major split between language varieties, dialects, or language groups.
-
C.
recognizedAsDistinctLanguageFrom
Indicates that one language is formally acknowledged or treated as a separate and distinct language from another, rather than as a dialect or variant of it.
-
D.
typicalLanguages
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
E.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
- 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_69f224868fa8819099127eaf8855a28f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a16debc8190a12f5f65ced055d7 |
completed | May 2, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 7:45 p.m.