Triple
T7077464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunflower State |
E164854
|
entity |
| Predicate | hasRegionTypeOfReferent |
P1828
|
FINISHED |
| Object | landlocked state |
—
|
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: landlocked state | Statement: [Sunflower State, hasRegionTypeOfReferent, landlocked state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionTypeOfReferent Context triple: [Sunflower State, hasRegionTypeOfReferent, landlocked state]
-
A.
isRegionOf
Indicates that one entity is a geographic or administrative region belonging to, contained within, or associated with another entity.
-
B.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
C.
refersToStateInRegion
Indicates that one entity denotes or references a specific state located within a particular region.
-
D.
hasRegionProperty
Indicates that a region is associated with a specific property or characteristic.
-
E.
regionType
chosen
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
- 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_69c6887cbc6c8190bdfac42d940f4d8a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4ee29288190a9a3fa7a6c713d8f |
completed | March 27, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:40 p.m.