Triple
T9606418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English in Uganda |
E231981
|
entity |
| Predicate | usedMoreIn |
P68012
|
FINISHED |
| Object | urban areas |
—
|
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: urban areas | Statement: [English in Uganda, usedMoreIn, urban areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedMoreIn Context triple: [English in Uganda, usedMoreIn, urban areas]
-
A.
usedOver
Indicates that one entity has been utilized, applied, or consumed in relation to another entity, typically as a resource, medium, or tool in a particular context or period.
-
B.
usedDuring
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
-
C.
usageAmong
chosen
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
D.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
E.
usedTerm
Indicates that one entity employed, referenced, or applied a particular term in some context.
- 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_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. |
Created at: March 30, 2026, 8:08 p.m.