Triple
T13909027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | encomenderos in the Americas |
E334434
|
entity |
| Predicate | associatedWithAbuse |
P54348
|
FINISHED |
| Object | forced labor |
—
|
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: forced labor | Statement: [encomenderos in the Americas, associatedWithAbuse, forced labor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAbuse Context triple: [encomenderos in the Americas, associatedWithAbuse, forced labor]
-
A.
associatedWithUse
Indicates a relationship where one entity is connected to or involved in the use or utilization of another entity.
-
B.
associatedWithSubstance
Indicates that one entity has a relevant connection or involvement with a particular substance, such as use, presence, exposure, or composition.
-
C.
associatedWithAccusation
Indicates a relationship where an entity is linked or connected to a specific accusation or charge.
-
D.
illegalActivityAssociatedWith
chosen
Indicates that there is a connection between an entity and an unlawful or criminal activity.
-
E.
associatedWithReport
Indicates that an entity has a connection or linkage to a specific report, such as being referenced in, contributing to, or otherwise related to that report.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2721ec6c8190888f4a9d004eb8e0 |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.