Triple
T22325192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | airag |
E551883
|
entity |
| Predicate | regionallySimilarTo |
P72140
|
FINISHED |
| Object | kumis |
—
|
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: kumis | Statement: [airag, regionallySimilarTo, kumis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionallySimilarTo Context triple: [airag, regionallySimilarTo, kumis]
-
A.
regionallyDistinctFrom
Indicates that two entities differ from each other in characteristics or classification based on their geographic or regional context.
-
B.
isRegionalAlternativeTo
chosen
Indicates that one entity serves as a counterpart or substitute for another within a specific geographic region or local context.
-
C.
regionallyAssociatedWith
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
D.
regionCorrespondsRoughlyTo
Indicates that one region approximately matches or aligns with another in location, extent, or boundaries, but not with precise or exact correspondence.
-
E.
isInSameRegionAs
Indicates that two entities are located within the same defined geographic or administrative region.
- 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_69e11e482f788190b78d1588fc26d606 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15767425481909547bfe294fe06de |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:42 p.m.