Triple
T959970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korean Peninsula |
E20710
|
entity |
| Predicate | politicallyDividedInto |
P21865
|
FINISHED |
| Object | two sovereign states |
—
|
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: two sovereign states | Statement: [Korean Peninsula, politicallyDividedInto, two sovereign states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicallyDividedInto Context triple: [Korean Peninsula, politicallyDividedInto, two sovereign states]
-
A.
politicalDivision
Indicates that one entity is a governmental or administrative subdivision or jurisdiction within the territory or authority of another entity.
-
B.
politicalBlocOnOneSide
Indicates that the entities belong to the same political bloc or coalition aligned on one side of a political division or conflict.
-
C.
dividedStatesInto
Indicates that one entity partitioned another entity into multiple distinct states or regions.
-
D.
historicallyDividedInto
Indicates that an entity was separated into multiple distinct parts or regions during a past historical period.
-
E.
wasDividedByTreaty
Indicates that an entity (such as a territory or region) was partitioned or separated as the result of a formal treaty or agreement.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b412f9f48190be123e8c20f38962 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a2e23c8190b932fe88b02f995d |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.