Triple
T586461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borneo |
E15167
|
entity |
| Predicate | rankingByArea |
P1170
|
FINISHED |
| Object | third-largest island in the world |
—
|
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 in the world | Statement: [Borneo, rankingByArea, third-largest island in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingByArea Context triple: [Borneo, rankingByArea, third-largest island in the world]
-
A.
areaRank
chosen
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
B.
continentRankByArea
Indicates the relative position of a continent in an ordered list based on its total land area.
-
C.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
D.
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).
-
E.
regionRankContext
Indicates the relative ranking or position of something within a specific geographic or regional context.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9a46388190a094b9ebf8dec397 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494ca68448190a516b9c3525d8916 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.