Triple
T184930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cultivation System |
E3959
|
entity |
| Predicate | socialEffect |
P4312
|
FINISHED |
| Object | widespread exploitation of peasants |
—
|
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: widespread exploitation of peasants | Statement: [Cultivation System, socialEffect, widespread exploitation of peasants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialEffect Context triple: [Cultivation System, socialEffect, widespread exploitation of peasants]
-
A.
socialImpact
chosen
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
B.
socialSystem
Indicates a relationship where entities are organized into a structured set of social roles, norms, and interactions that govern their collective behavior.
-
C.
politicalRepercussion
Indicates that an action, event, or decision leads to consequences or fallout within a political context, such as shifts in power, public opinion, or policy.
-
D.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
E.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2592867108190b5d316c055575449 |
completed | Feb. 28, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69a2566fb08c81908faff2fde552105d |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.