Triple
T25237566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windrush generation |
E632379
|
entity |
| Predicate | typicalSettlementArea |
P188863
|
FINISHED |
| Object | Brixton |
—
|
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: Brixton | Statement: [Windrush generation, typicalSettlementArea, Brixton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSettlementArea Context triple: [Windrush generation, typicalSettlementArea, Brixton]
-
A.
typicalSettlement
Indicates that the subject is a common or characteristic type of settlement typically found in the context of the object.
-
B.
traditionalSettlementArea
Indicates that an area is recognized as a traditional settlement zone associated with a particular group or community.
-
C.
mainSettlement
Indicates that one settlement serves as the primary or most important settlement associated with a given area, region, or administrative unit.
-
D.
traditionalSettlement
Indicates that an entity is a settlement characterized by long-established, customary, or historically rooted patterns of habitation and land use.
-
E.
settledRegion
Indicates that an entity has established a lasting presence or habitation within a particular geographic region.
- F. None of above. chosen
Provenance (4 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_69e75a8ec5f88190b9eba06ae42b413a |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69fbaf18085481908c774e8f8bbb9a41 |
completed | May 6, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69fbaebbb7f88190b4edfd9b83550aad |
completed | May 6, 2026, 9:12 p.m. |
Created at: April 21, 2026, 1:07 p.m.