Triple
T9606415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English in Uganda |
E231981
|
entity |
| Predicate | socioeconomicRole |
P89201
|
FINISHED |
| Object | language of upward mobility |
—
|
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: language of upward mobility | Statement: [English in Uganda, socioeconomicRole, language of upward mobility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socioeconomicRole Context triple: [English in Uganda, socioeconomicRole, language of upward mobility]
-
A.
urbanRole
Indicates the function, status, or role that an entity holds within an urban or city context.
-
B.
hasEconomicRole
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
-
C.
ethnicRole
Indicates a role, function, or social position that is specifically associated with or defined by an entity’s ethnicity.
-
D.
ethnographicRole
Indicates the role or function an entity holds within an ethnographic context, such as a cultural, social, or research-related position.
-
E.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
- 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_69ca8485a90c819094fe40b42fde9d70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a6006d48190adc03306533b9be6 |
completed | April 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a6fd2481908efd131e207b8143 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:08 p.m.