Triple
T9572788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nat Turner |
E230964
|
entity |
| Predicate | numberOfPeopleKilledInRebellion |
P63692
|
FINISHED |
| Object | approximately 55 to 60 white 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: approximately 55 to 60 white people | Statement: [Nat Turner, numberOfPeopleKilledInRebellion, approximately 55 to 60 white people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPeopleKilledInRebellion Context triple: [Nat Turner, numberOfPeopleKilledInRebellion, approximately 55 to 60 white people]
-
A.
facedRebellionBy
Indicates that an entity experienced opposition or an uprising initiated by another entity.
-
B.
numberOfVictimsKilled
chosen
Indicates the count of victims who were killed as a result of the referenced event or action.
-
C.
estimatedPrisonersKilled
Indicates the estimated number of prisoners who were killed in a given context or event.
-
D.
Tambov Rebellion
Indicates an organized uprising or revolt occurring in or associated with Tambov, typically involving armed resistance against an established authority.
-
E.
resultOfUprising
Indicates that something exists or occurs as a consequence or outcome of an uprising or rebellion.
- 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_69ca847f22188190a56e4a97625bef22 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd998d79cc8190b94e5953915a5fa4 |
completed | April 1, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69ccd59b960c8190966a8870a2426bd5 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:04 p.m.