Triple
T10345085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French–Native American wars |
E243723
|
entity |
| Predicate | primaryCauses |
P57423
|
FINISHED |
| Object | control of the fur trade |
—
|
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: control of the fur trade | Statement: [French–Native American wars, primaryCauses, control of the fur trade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCauses Context triple: [French–Native American wars, primaryCauses, control of the fur trade]
-
A.
primaryCauseCategory
Indicates the main type or classification of cause responsible for an outcome or event.
-
B.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
C.
primaryDisease
Indicates that a disease is the main or principal medical condition affecting an entity, as opposed to secondary or comorbid conditions.
-
D.
causeOfIllness
Indicates that one entity is the reason or source responsible for another entity’s illness or disease.
-
E.
primaryIssue
chosen
Indicates that the related item is the main or most important issue among a set of issues.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9228cd88190bcd94b85537233c1 |
completed | April 7, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69d4df9dc3208190bf1bd106f44f6202 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:56 a.m.