Triple
T10171188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afro-Eurasia |
E235333
|
entity |
| Predicate | isLargestContinuousLandmassOnEarth |
P11013
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Afro-Eurasia, isLargestContinuousLandmassOnEarth, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLargestContinuousLandmassOnEarth Context triple: [Afro-Eurasia, isLargestContinuousLandmassOnEarth, true]
-
A.
isLargestContiguousLandmass
chosen
Indicates that one landmass is the largest single, unbroken continuous area of land compared to all other landmasses in the relevant context.
-
B.
hasLargestContinuousLandAreaOn
Indicates that an entity possesses the greatest uninterrupted expanse of land on a specified geographic region or surface compared to all other entities.
-
C.
majorLandmasses
Indicates that the related entities are the primary, large continuous expanses of land on a planetary surface.
-
D.
continentType
Indicates that one entity is classified as a specific type or category of continent in relation to another entity.
-
E.
largestRegionByAreaIn
Indicates that one region is the largest by geographic area among all regions within a specified containing area.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9e4e0c819097dceb7bf7757948 |
completed | April 2, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.