Triple
T1819006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State House of Kenya |
E40498
|
entity |
| Predicate | typeOfResidence |
P542
|
FINISHED |
| Object | presidential residence |
—
|
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: presidential residence | Statement: [State House of Kenya, typeOfResidence, presidential residence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfResidence Context triple: [State House of Kenya, typeOfResidence, presidential residence]
-
A.
residenceType
chosen
Indicates the kind or category of dwelling or living arrangement associated with an entity.
-
B.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
-
C.
residencyPattern
Indicates the typical way an entity resides or occupies a place over time, such as its usual location, duration, or frequency of stay.
-
D.
hasResidenceIn
Indicates that an entity lives or maintains a primary dwelling in a specified location.
-
E.
isResidential
Indicates that something is used or designated primarily for people to live in, rather than for commercial, industrial, or other non-living purposes.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d884548190a19cf3a6b5ae9d48 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.