Triple
T25160983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PKI |
E626436
|
entity |
| Predicate | majorForceIn |
P404
|
FINISHED |
| Object | Indonesian politics in the 1950s |
—
|
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: Indonesian politics in the 1950s | Statement: [PKI, majorForceIn, Indonesian politics in the 1950s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorForceIn Context triple: [PKI, majorForceIn, Indonesian politics in the 1950s]
-
A.
majorPowerIn
chosen
Indicates that an entity holds significant political, economic, or military influence within a specified domain, region, or context.
-
B.
majorPowerUntil
Indicates that an entity functioned as a major power or dominant force up to, but not beyond, a specified time or event.
-
C.
majorBelligerent
Indicates that an entity is a primary or principal participant in a conflict, war, or large-scale hostile engagement.
-
D.
strengthGovernmentForces
Indicates the level or degree of military or coercive power held or exerted by government forces in a given context.
-
E.
madeMajorPower
Indicates that one entity caused or enabled another entity to attain the status or influence of a major power.
- 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_69e2ff2834ec8190b0872e2ec3d76023 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 18, 2026, 6:31 a.m.