Triple
T4558194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navigation Act of 1651 |
E120528
|
entity |
| Predicate | effectOnNetherlands |
P27109
|
FINISHED |
| Object | threatened Dutch commercial interests |
—
|
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: threatened Dutch commercial interests | Statement: [Navigation Act of 1651, effectOnNetherlands, threatened Dutch commercial interests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnNetherlands Context triple: [Navigation Act of 1651, effectOnNetherlands, threatened Dutch commercial interests]
-
A.
effectOnDutchRepublic
chosen
Indicates the impact or consequences that something has on the Dutch Republic.
-
B.
effectOnUnitedStates
Indicates the impact, influence, or consequences that something has on the United States.
-
C.
resultForDutchRepublic
Indicates the outcome or consequence that pertains specifically to the Dutch Republic in a given event or context.
-
D.
effectOnSpain
Indicates a relationship where one entity produces an influence, change, or consequence specifically affecting Spain.
-
E.
areaInundatedNetherlands
Indicates the extent of land in the Netherlands that is covered or flooded by water.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd5829cc34819086ad2ae58446502e |
completed | March 20, 2026, 2:22 p.m. |
| PD | Predicate disambiguation | batch_69bd52254c648190a5144cfe8fa7e409 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.