Triple
T25162427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentina and Chile |
E626476
|
entity |
| Predicate | shareLandscapeType |
P5696
|
FINISHED |
| Object | mountainous regions |
—
|
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: mountainous regions | Statement: [Argentina and Chile, shareLandscapeType, mountainous regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareLandscapeType Context triple: [Argentina and Chile, shareLandscapeType, mountainous regions]
-
A.
sharesTypeWith
Indicates that two entities belong to the same type or category.
-
B.
sharesType
Indicates that two or more entities have the same type or belong to the same category.
-
C.
sharesUniverseWith
Indicates that two entities exist within the same fictional or narrative universe, implying shared continuity, setting, or canon.
-
D.
sharesFeatureWith
chosen
Indicates that two entities have at least one common attribute, property, or characteristic in common.
-
E.
sharesResourceType
Indicates that two or more entities use or are associated with the same type or category of resource.
- 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_69e2ff2834ec8190b0872e2ec3d76023 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 18, 2026, 6:31 a.m.