Triple
T1742098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherokee Nation (historical) |
E38254
|
entity |
| Predicate | populationAffectedByRemoval |
P3838
|
FINISHED |
| Object | thousands of Cherokee people |
—
|
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: thousands of Cherokee people | Statement: [Cherokee Nation (historical), populationAffectedByRemoval, thousands of Cherokee people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationAffectedByRemoval Context triple: [Cherokee Nation (historical), populationAffectedByRemoval, thousands of Cherokee people]
-
A.
areaDestroyed
Indicates that a specified portion or region has been damaged or ruined to the point of destruction.
-
B.
affectedCity
Indicates that a particular city is impacted or influenced by a specified event, action, or condition.
-
C.
numberOfEvacuated
Indicates the total count of individuals who have been evacuated from a location or situation.
-
D.
affectedCountry
Indicates that a particular country is impacted or influenced by an event, action, or condition.
-
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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab3c2559ac8190905186406fcaccb9 |
completed | March 6, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69aa61c4023c819099cbe439aefda71f |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.