Triple
T460950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Native Americans |
E7334
|
entity |
| Predicate | populationAffectedBy |
P3838
|
FINISHED |
| Object | European colonization of the Americas |
—
|
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: European colonization of the Americas | Statement: [Native Americans, populationAffectedBy, European colonization of the Americas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationAffectedBy Context triple: [Native Americans, populationAffectedBy, European colonization of the Americas]
-
A.
affectedCountry
Indicates that a particular country is impacted or influenced by an event, action, or condition.
-
B.
affectedCity
Indicates that a particular city is impacted or influenced by a specified event, action, or condition.
-
C.
displacedPeopleEstimate
Indicates an estimated number of people who have been forced to leave their homes or usual places of residence due to a particular event or situation.
-
D.
casualtiesImpact
Indicates how the number or severity of casualties affects or influences another factor, situation, or outcome.
-
E.
demographicImpact
chosen
Indicates how an action, event, or condition affects the size, structure, or composition of a population.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efbed5b88190a45716812eb4cfdf |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede75b6c81908350103d21f22a03 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.