Triple
T17116452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Thomas, U.S. Virgin Islands |
E415350
|
entity |
| Predicate | transferToUnitedStatesYear |
P8725
|
FINISHED |
| Object | 1917 |
—
|
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: 1917 | Statement: [St. Thomas, U.S. Virgin Islands, transferToUnitedStatesYear, 1917]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transferToUnitedStatesYear Context triple: [St. Thomas, U.S. Virgin Islands, transferToUnitedStatesYear, 1917]
-
A.
entryToUnitedStatesDate
Indicates the date on which an entity entered the United States.
-
B.
yearOfImmigration
Indicates the specific year in which an entity immigrated to a new country or region.
-
C.
transitionYear
chosen
Indicates the specific year in which a change, shift, or transition from one state, condition, or phase to another occurs.
-
D.
deportationYear
Indicates the year in which an entity was deported from a country or territory.
-
E.
emigratedToState
Indicates that a person or group moved from their previous country or region to take up residence in a specified state.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e80660048190832d8f91415dd7d7 |
completed | April 18, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.