Triple
T27147838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mro |
E681997
|
entity |
| Predicate | livelihoodChallenges |
P161906
|
FINISHED |
| Object | land dispossession |
—
|
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: land dispossession | Statement: [Mro, livelihoodChallenges, land dispossession]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: livelihoodChallenges Context triple: [Mro, livelihoodChallenges, land dispossession]
-
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.
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.
-
C.
livelihood
Indicates that one entity serves as the primary means of support, income, or subsistence for another entity.
-
D.
hasAgriculturalChallenge
Indicates that an entity is experiencing or associated with a difficulty, problem, or obstacle related to agriculture or farming activities.
-
E.
lifeSituation
Indicates the general circumstances, conditions, or context in which an entity’s life currently exists or unfolds.
- 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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f624c7ad888190b57bb987a8202789 |
completed | May 2, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61fa35ac48190890102c348ed81a0 |
completed | May 2, 2026, 4 p.m. |
Created at: April 27, 2026, 9:12 a.m.