Triple
T21858868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boljun necropolis |
E539704
|
entity |
| Predicate | hasLanguageRegionContext |
P145951
|
FINISHED |
| Object | South Slavic |
—
|
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: South Slavic | Statement: [Boljun necropolis, hasLanguageRegionContext, South Slavic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageRegionContext Context triple: [Boljun necropolis, hasLanguageRegionContext, South Slavic]
-
A.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
B.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
C.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
D.
hasTraditionalLanguageRegion
Indicates the geographic region traditionally associated with the use or origin of a particular language.
-
E.
nativeLanguageContext
Indicates the relationship in which a language functions as the primary or native linguistic context for an entity’s communication or interpretation.
- F. None of above. chosen
Provenance (4 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_69e0c47829648190bbe2d1d7033768ec |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0d63944d88190b6bd5e6ba4cc8ec1 |
completed | April 28, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69e6be9394f88190945ddd1dc004d29d |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6d054737081908aa7112975b77475 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 6:56 p.m.