Triple
T28886405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karenni |
E732572
|
entity |
| Predicate | alsoAssociatedWithRegion |
P12445
|
FINISHED |
| Object | southern Shan State |
—
|
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: southern Shan State | Statement: [Karenni, alsoAssociatedWithRegion, southern Shan State]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoAssociatedWithRegion Context triple: [Karenni, alsoAssociatedWithRegion, southern Shan State]
-
A.
regionOfAssociation
Indicates a broader geographic or spatial area with which an entity is functionally, contextually, or organizationally associated.
-
B.
regionallyAssociatedWith
chosen
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
C.
associatedRegionFeature
Indicates that something is linked or connected to a particular geographic or regional feature.
-
D.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
E.
associatedAdministrativeRegion
Indicates that an entity is linked to, or falls under the jurisdiction of, a particular 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_69f05b07bdec819080cadfe147aa1f25 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65a72a4d08190a45476cd7a50a7cc |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 7:50 a.m.