Triple
T35906240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenyatta Day |
E1038478
|
entity |
| Predicate | hasSuccessorHoliday |
P9806
|
FINISHED |
| Object | Mashujaa Day |
—
|
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: Mashujaa Day | Statement: [Kenyatta Day, hasSuccessorHoliday, Mashujaa Day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuccessorHoliday Context triple: [Kenyatta Day, hasSuccessorHoliday, Mashujaa Day]
-
A.
successorHolidayDate
Indicates that one holiday’s date directly follows or succeeds another holiday’s date in a temporal sequence.
-
B.
successorHolidayEnglishName
Indicates that one holiday is followed by another holiday, specifying the English name of the subsequent holiday in the sequence.
-
C.
predecessorHoliday
chosen
Indicates that one holiday directly precedes another in a temporal or calendrical sequence.
-
D.
hasCommonHoliday
Indicates that two entities share at least one holiday that is observed or celebrated in common.
-
E.
hasHolidayAssociation
Indicates a relationship where something is connected or related to a holiday, such as by theme, usage, or occurrence.
- 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_69fffc783b648190bcd7df017514d206 |
completed | May 10, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69fffc03fa24819099e12413dc6e0afd |
completed | May 10, 2026, 3:31 a.m. |
Created at: May 3, 2026, 4:07 p.m.