Triple
T31813535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke Street, Kingston |
E812073
|
entity |
| Predicate | hasNotableNearbyArea |
P39585
|
FINISHED |
| Object | Parliament area of Kingston |
—
|
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: Parliament area of Kingston | Statement: [Duke Street, Kingston, hasNotableNearbyArea, Parliament area of Kingston]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableNearbyArea Context triple: [Duke Street, Kingston, hasNotableNearbyArea, Parliament area of Kingston]
-
A.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
-
B.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
-
C.
hasNotableNearbyEntity
chosen
Indicates that one entity has another significant or noteworthy entity located in its close physical or contextual proximity.
-
D.
hasNearbyHistoricArea
Indicates that one entity is located close to another entity that is designated as a historic area.
-
E.
notableAreaWithin
Indicates that one area is a particularly significant or noteworthy part located inside another, larger area.
- 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_69f348e846c081908eb468a0665afd55 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a00be8ee4bc8190b795d9606f0e490c |
completed | May 10, 2026, 5:21 p.m. |
| PD | Predicate disambiguation | batch_6a00bde163c88190867104bd08cac2ee |
completed | May 10, 2026, 5:18 p.m. |
Created at: April 30, 2026, 11:44 p.m.