Triple
T14971062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayei people |
E373318
|
entity |
| Predicate | livelihoodDependenceOn |
P29524
|
FINISHED |
| Object | seasonal flooding |
—
|
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: seasonal flooding | Statement: [Bayei people, livelihoodDependenceOn, seasonal flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: livelihoodDependenceOn Context triple: [Bayei people, livelihoodDependenceOn, seasonal flooding]
-
A.
livelihood
chosen
Indicates that one entity serves as the primary means of support, income, or subsistence for another entity.
-
B.
agriculturalDependence
Indicates that one entity relies on another for agricultural resources, production, or support.
-
C.
livelihoodVulnerability
Indicates the degree to which an entity’s means of making a living are exposed or susceptible to harm, disruption, or loss.
-
D.
livelihoodChange
Indicates a change in a person’s or group’s means of making a living, such as improvements, declines, or shifts in income-generating activities.
-
E.
socioEconomicBase
Indicates a foundational socio-economic relationship where one entity serves as the economic or social basis, support, or underlying structure for another.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e59a7c8190a1634a706ea68fda |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:49 a.m.