Triple
T9418630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherokee |
E227091
|
entity |
| Predicate | estimatedDeathsDuringTrailOfTears |
P700
|
FINISHED |
| Object | Thousands of 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 people | Statement: [Cherokee, estimatedDeathsDuringTrailOfTears, Thousands of people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedDeathsDuringTrailOfTears Context triple: [Cherokee, estimatedDeathsDuringTrailOfTears, Thousands of people]
-
A.
NativeAmerican casualties
Indicates the number of Native Americans who were killed, wounded, or otherwise harmed in a specific conflict or violent event.
-
B.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
C.
deathTollEstimate
chosen
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
D.
casualtiesKilledUS
Indicates that the relationship specifies the number of U.S. individuals who were killed as casualties in an event or incident.
-
E.
UScasualties
Indicates the number or occurrence of casualties suffered by the United States in a given conflict, event, or situation.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68cd1e3481909abcb715e2398120 |
completed | April 1, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:48 p.m.