Triple
T30249265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | gavit |
E769149
|
entity |
| Predicate | isRegionallySpecificTo |
P108665
|
FINISHED |
| Object | historical Armenia |
—
|
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: historical Armenia | Statement: [gavit, isRegionallySpecificTo, historical Armenia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRegionallySpecificTo Context triple: [gavit, isRegionallySpecificTo, historical Armenia]
-
A.
isRegional
chosen
Indicates that something pertains to, is characteristic of, or is limited to a specific geographic region or area.
-
B.
hasRegionalVariationsIn
Indicates that something exhibits different forms, versions, or characteristics depending on the geographic region.
-
C.
regionalVariantOf
Indicates that one entity is a version or form of another that is specific to a particular geographic region or locale.
-
D.
regionallyDistinctFrom
Indicates that two entities differ from each other in characteristics or classification based on their geographic or regional context.
-
E.
isRegionalAlternativeTo
Indicates that one entity serves as a counterpart or substitute for another within a specific geographic region or local context.
- 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_69f224831dc08190b2e569b987264057 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68079a50c819090a11d215f3dd4b0 |
completed | May 2, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:40 p.m.