Triple
T1782682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emma Goldman |
E39322
|
entity |
| Predicate | yearOfDeportation |
P22994
|
FINISHED |
| Object | 1919 |
—
|
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: 1919 | Statement: [Emma Goldman, yearOfDeportation, 1919]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfDeportation Context triple: [Emma Goldman, yearOfDeportation, 1919]
-
A.
deportationYear
chosen
Indicates the year in which an entity was deported from a country or territory.
-
B.
yearOfEmigration
Indicates the specific year in which an entity permanently left its country or place of origin to settle elsewhere.
-
C.
deportedTo
Indicates that an authority forcibly removed a person from one place or country and sent them to another specified destination.
-
D.
deportedBy
Indicates that an entity was expelled or removed from a country or territory by a specific authority, agent, or organization.
-
E.
deportedUnder
Indicates that an entity was deported in accordance with, or by authority of, a specific law, policy, program, or legal provision.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.