Triple
T11056877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Tubman |
E261398
|
entity |
| Predicate | helpedEnslavedPeopleEscape |
P24359
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Harriet Tubman, helpedEnslavedPeopleEscape, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpedEnslavedPeopleEscape Context triple: [Harriet Tubman, helpedEnslavedPeopleEscape, true]
-
A.
helpedEscape
chosen
Indicates that one entity assisted another in getting away from confinement, danger, or pursuit.
-
B.
wasFormerlyEnslaved
Indicates that an entity was previously held in a condition of slavery or bondage but is no longer enslaved.
-
C.
beneficiariesOfEmancipation
Indicates that the subject is a person or group who gains rights, freedoms, or advantages as a result of an emancipation event or process.
-
D.
wasEnslavedIn
Indicates that an entity was held in a state of slavery within a specified place or context.
-
E.
numberOfSerfsFreed
Indicates the quantity of serfs that were liberated from serfdom in a given context or event.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a2404c819090cb0825a67a64fa |
completed | April 9, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69d7440da46c8190a77380d5d747ac9c |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:26 p.m.