Triple
T6619796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Borough of Barnet |
E149645
|
entity |
| Predicate | areaRankInLondon |
P1170
|
FINISHED |
| Object | one of the largest by area |
—
|
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 largest by area | Statement: [London Borough of Barnet, areaRankInLondon, one of the largest by area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankInLondon Context triple: [London Borough of Barnet, areaRankInLondon, one of the largest by area]
-
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.
areaRank
chosen
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
D.
hasLondonBorough
Indicates that an entity includes, contains, or is associated with a specific London borough as one of its administrative subdivisions.
-
E.
hasOuterLondonBorough
Indicates that an entity is associated with, located in, or administered by a borough that is part of Outer London.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:58 p.m.