Triple
T38088030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Republic of South Korea |
E951025
|
entity |
| Predicate | mainOppositionForce |
P4567
|
FINISHED |
| Object | military leadership under Park Chung-hee |
—
|
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: military leadership under Park Chung-hee | Statement: [Second Republic of South Korea, mainOppositionForce, military leadership under Park Chung-hee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainOppositionForce Context triple: [Second Republic of South Korea, mainOppositionForce, military leadership under Park Chung-hee]
-
A.
opposingAlliance
Indicates that two entities belong to rival or mutually opposed alliances or factions.
-
B.
opposingForce
chosen
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
-
C.
hasOpposingFaction
Indicates that one faction stands in opposition or conflict to another faction.
-
D.
oppositionAlliance
Indicates a relationship where entities form or belong to an alliance that is collectively opposed to another entity or group.
-
E.
primaryOpposingForceSize
Indicates the size or magnitude of the main opposing force acting against a subject in a given 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_69f76f03a3608190a73fd6df87c792a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc4748843c8190931432653be4890c |
completed | May 7, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69fc45646ce481908caf292ff9f06e15 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.