Triple
T1030751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewis and Harris |
E22243
|
entity |
| Predicate | rankInBritishIslesByArea |
P24199
|
FINISHED |
| Object | third-largest island of the British Isles |
—
|
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: third-largest island of the British Isles | Statement: [Lewis and Harris, rankInBritishIslesByArea, third-largest island of the British Isles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInBritishIslesByArea Context triple: [Lewis and Harris, rankInBritishIslesByArea, third-largest island of the British Isles]
-
A.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
B.
continentRankByArea
Indicates the relative position of a continent in an ordered list based on its total land area.
-
C.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
D.
landAreaSquareMiles
Indicates the size of a geographic area measured in square miles.
-
E.
areaOfMemberStatesApprox
Indicates the approximate total geographic area collectively covered by the member states of a given organization or grouping.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95d35888190a20593a278175df7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7276180819085c6b23501a6a6e0 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b95bb5908190ad1d5f5e0d8f664d |
completed | March 1, 2026, 10:10 p.m. |
Created at: March 1, 2026, 7:41 p.m.