Triple
T3944489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellesmere Island |
E92112
|
entity |
| Predicate | rankByAreaInCanada |
P37999
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Ellesmere Island, rankByAreaInCanada, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInCanada Context triple: [Ellesmere Island, rankByAreaInCanada, 3]
-
A.
hasPopulationRankInCanada
Indicates the relative position of an entity’s population size compared to other entities within Canada.
-
B.
rankByAreaInCanadaIslands
chosen
Indicates the numerical position of an island in Canada when all Canadian islands are ordered by their land area from largest to smallest.
-
C.
largestProvinceByArea
Indicates that one province has the greatest land area compared to all other provinces within a specified region or country.
-
D.
chartPositionCanada
Indicates the position or ranking of something on a chart specifically within Canada.
-
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_69aed965502c8190904ebad1203a4ae8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee764235081909309b3c982f322a9 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:24 p.m.