Triple
T16379180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adeola |
E397754
|
entity |
| Predicate | frequencyCategoryInNigeria |
P123164
|
FINISHED |
| Object | common name |
—
|
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: common name | Statement: [Adeola, frequencyCategoryInNigeria, common name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyCategoryInNigeria Context triple: [Adeola, frequencyCategoryInNigeria, common name]
-
A.
frequencyCategory
Indicates how often an action, event, or relationship occurs, typically by assigning it to a qualitative frequency level (e.g., rare, occasional, frequent).
-
B.
frequencyInUS
Indicates how often something occurs, appears, or is used within the United States.
-
C.
frequencyRegion
Indicates that something is associated with, occurs within, or is characterized by a particular range or band of frequencies.
-
D.
frequencyBand
Indicates the specific range of frequencies within which a signal, measurement, or phenomenon is defined or operates.
-
E.
frequencyCategoryInSpain
Indicates the categorized level of how often something occurs or is observed within Spain.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e319da3c6c8190a9ccf744996c31e8 |
completed | April 18, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69e226f94dd48190b7b8e0e983738a67 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:08 a.m.