Triple
T604823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhode Island |
E11571
|
entity |
| Predicate | isSmallestU.S.StateBy |
P14659
|
FINISHED |
| Object | area |
—
|
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: area | Statement: [Rhode Island, isSmallestU.S.StateBy, area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSmallestU.S.StateBy Context triple: [Rhode Island, isSmallestU.S.StateBy, area]
-
A.
isSmallestByAreaIn
chosen
Indicates that an entity has the smallest area among all comparable entities within a specified set, group, or context.
-
B.
largestStateByArea
Indicates that a state is the one with the greatest land area within a specified set or region.
-
C.
stateOrTerritory
Indicates that one entity is a state or territory that is politically or administratively associated with another entity.
-
D.
isSmallestCountryIn
Indicates that a country is the smallest (by a specified measure, typically area) among all countries within a given region or set.
-
E.
largestStateByPopulation
Indicates that the subject is the state with the highest population among a specified set of states or within a given region.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df34abc8190a578c8c2ab3d28e4 |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cf8fc1c81908a9c7df552aa1a59 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.