Triple
T5020410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Borough of Islington |
E112835
|
entity |
| Predicate | populationRankInLondon |
P1169
|
FINISHED |
| Object | one of the most densely populated boroughs |
—
|
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: one of the most densely populated boroughs | Statement: [London Borough of Islington, populationRankInLondon, one of the most densely populated boroughs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInLondon Context triple: [London Borough of Islington, populationRankInLondon, one of the most densely populated boroughs]
-
A.
hasPopulationRankInUK
Indicates the relative position of an entity’s population size compared to other entities within the United Kingdom.
-
B.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
C.
populationRank
chosen
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
D.
populationRankAfter
Indicates the relative position of an entity in a population-based ordering that comes after another entity’s population rank.
-
E.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd736399ac8190aa38efc4b4edc6a2 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.