Triple
T8657020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akha people |
E205443
|
entity |
| Predicate | livelihoodChange |
P84164
|
FINISHED |
| Object | increasing involvement in cash-crop agriculture |
—
|
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: increasing involvement in cash-crop agriculture | Statement: [Akha people, livelihoodChange, increasing involvement in cash-crop agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: livelihoodChange Context triple: [Akha people, livelihoodChange, increasing involvement in cash-crop agriculture]
-
A.
livelihood
Indicates that one entity serves as the primary means of support, income, or subsistence for another entity.
-
B.
livelihoodVulnerability
Indicates the degree to which an entity’s means of making a living are exposed or susceptible to harm, disruption, or loss.
-
C.
landUseChangeTo
Indicates a transition in how a piece of land is used, from its previous use to a new designated use.
-
D.
occupationalChange
Indicates a change in a person’s job, profession, or occupational status over time.
-
E.
agriculturalImpact
Indicates the effect that an action, condition, or entity has on agricultural systems, productivity, or practices.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc484569788190aa41395854684e6f |
completed | March 31, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc473e44988190a3b02498e5fff668 |
completed | March 31, 2026, 10:14 p.m. |
Created at: March 30, 2026, 6:30 p.m.