Triple
T36663241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yedina |
E905189
|
entity |
| Predicate | livelihoodAdaptation |
P186131
|
FINISHED |
| Object | adaptation to fluctuating lake levels |
—
|
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: adaptation to fluctuating lake levels | Statement: [Yedina, livelihoodAdaptation, adaptation to fluctuating lake levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: livelihoodAdaptation Context triple: [Yedina, livelihoodAdaptation, adaptation to fluctuating lake levels]
-
A.
livelihoodVulnerability
Indicates the degree to which an entity’s means of making a living are exposed or susceptible to harm, disruption, or loss.
-
B.
livelihoodChallenges
Indicates difficulties or obstacles that negatively affect an entity’s ability to secure or maintain its means of living or income.
-
C.
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.
-
D.
livelihoodArea
Indicates the area or domain in which an entity earns its living or sustains its means of support.
-
E.
livelihood
Indicates that one entity serves as the primary means of support, income, or subsistence for another entity.
- 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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c83f5960819089610ed39c839678 |
completed | May 3, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
| PDg | Predicate description generation | batch_69f7c776b4088190bef550c869da530d |
completed | May 3, 2026, 10:08 p.m. |
Created at: May 3, 2026, 4:12 p.m.