Triple
T29438265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speaker of the Senate of Kenya |
E746638
|
entity |
| Predicate | precedesInOrderOfPrecedence |
P1803
|
FINISHED |
| Object | most senators |
—
|
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: most senators | Statement: [Speaker of the Senate of Kenya, precedesInOrderOfPrecedence, most senators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: precedesInOrderOfPrecedence Context triple: [Speaker of the Senate of Kenya, precedesInOrderOfPrecedence, most senators]
-
A.
confersPrecedenceIn
Indicates that one entity is granted higher priority, rank, or standing over another within a specified context or domain.
-
B.
belongsToOrderOfPrecedence
Indicates that one entity is assigned a specific position or rank within an established order of precedence relative to other entities.
-
C.
orderPrecedence
chosen
Indicates that one entity must come before another in a defined sequence or priority order.
-
D.
hasPrecedence
Indicates that one entity occurs, is considered, or is applied before another in order, priority, or importance.
-
E.
orderOfPrecedenceHigher
Indicates that one entity holds a higher rank or priority than another in an established order of precedence.
- 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 28, 2026, 3:18 p.m.