Triple
T948024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claes Maartenszen van Rosenvelt |
E20456
|
entity |
| Predicate | migrationDirection |
P4275
|
FINISHED |
| Object | Europe to North America |
—
|
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: Europe to North America | Statement: [Claes Maartenszen van Rosenvelt, migrationDirection, Europe to North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: migrationDirection Context triple: [Claes Maartenszen van Rosenvelt, migrationDirection, Europe to North America]
-
A.
migration
chosen
Indicates the movement of entities from one location or context to another, often across boundaries or over time.
-
B.
migrationPattern
Indicates the typical routes, timing, and destinations followed by entities as they move periodically from one location or region to another.
-
C.
migrationEvent
Indicates an event in which one or more entities move or relocate from one place or context to another, typically across defined boundaries or regions.
-
D.
migrationSpeed
Indicates the rate at which an entity moves from one location or region to another over a given period of time.
-
E.
translationDirection
Indicates the source and target languages involved in a translation, specifying the direction from the original language to the translated language.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3be19448190a8863fce3d152430 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b29f05f481908814bd11f235e9d0 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.