Triple
T35857439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State House, Nakuru |
E1036547
|
entity |
| Predicate | sisterResidence |
P75
|
FINISHED |
| Object | State House, Nairobi |
—
|
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: State House, Nairobi | Statement: [State House, Nakuru, sisterResidence, State House, Nairobi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sisterResidence Context triple: [State House, Nakuru, sisterResidence, State House, Nairobi]
-
A.
sisterInn
Indicates that one entity is the sister-in-law of another entity, typically through marriage to a sibling or being the sibling of a spouse.
-
B.
sisterHouse
Indicates that two houses or organizations are formally paired or affiliated as sister entities, typically sharing a close, cooperative relationship.
-
C.
sisterComplex
Indicates a strong, often excessive or romanticized emotional fixation or attraction that someone has toward their sister.
-
D.
sisterSettlement
Indicates that two settlements are formally paired or twinned, typically to promote cultural, social, or economic exchange.
-
E.
residence
chosen
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
- 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_69f76e1b4aa481909630373171eb5ec6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac23d1388190bdf9628b294943bd |
completed | May 3, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:06 p.m.