Triple
T35906243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenyatta Day |
E1038478
|
entity |
| Predicate | commemoratedPersonOffice |
P159053
|
FINISHED |
| Object | President of Kenya |
—
|
NE NERFINISHED |
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: President of Kenya | Statement: [Kenyatta Day, commemoratedPersonOffice, President of Kenya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commemoratedPersonOffice Context triple: [Kenyatta Day, commemoratedPersonOffice, President of Kenya]
-
A.
commemoratedPersonOccupation
Indicates the occupation or professional role held by the person who is being commemorated.
-
B.
commemoratesOffice
chosen
Indicates that one entity serves as a memorial or tribute to a particular office or official position.
-
C.
commemoratedPerson
Indicates that the subject serves as a memorial or tribute to the referenced person.
-
D.
commemoratedPersonNationality
Indicates the nationality of the person who is being commemorated.
-
E.
commemoratedFor
Indicates that one entity is honored, remembered, or celebrated because of a particular action, achievement, event, or characteristic associated with it.
- 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_69f76e2259608190bf6788a132e0d139 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:07 p.m.