Triple
T433873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonardo DiCaprio |
E9770
|
entity |
| Predicate | foundationFocus |
P31
|
FINISHED |
| Object | environmental protection |
—
|
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: environmental protection | Statement: [Leonardo DiCaprio, foundationFocus, environmental protection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foundationFocus Context triple: [Leonardo DiCaprio, foundationFocus, environmental protection]
-
A.
foundationPlace
Indicates the place where an organization, institution, or similar entity was originally founded or established.
-
B.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
D.
primaryFoot
Indicates which foot (e.g., left or right) serves as the main or dominant foot for an entity.
-
E.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ef0a008c8190ae0aa25e4df9c35f |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2edda55e88190b7c17ba94d7df1ce |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.