Triple
T30197857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division Two |
E767683
|
entity |
| Predicate | typicalGroundType |
P207217
|
FINISHED |
| Object | non-league football ground |
—
|
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: non-league football ground | Statement: [Division Two, typicalGroundType, non-league football ground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGroundType Context triple: [Division Two, typicalGroundType, non-league football ground]
-
A.
homeGroundType
Indicates the type or category of venue that serves as an entity’s designated home ground.
-
B.
ground
Indicates that one entity is in contact with or supported by the ground or a ground-like surface.
-
C.
typicalGroundElementSize
Indicates the usual or standard physical size of an element that is part of the ground or base layer in a given context.
-
D.
typicalLotType
Indicates that one entity is the standard or commonly occurring type of lot associated with another entity.
-
E.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 7:30 p.m.