Triple
T4177734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conservation International |
E86516
|
entity |
| Predicate | roleOfJennifer Morris |
P54240
|
FINISHED |
| Object | former President |
—
|
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: former President | Statement: [Conservation International, roleOfJennifer Morris, former President]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfJennifer Morris Context triple: [Conservation International, roleOfJennifer Morris, former President]
-
A.
MarilynMonroeRoleType
Indicates the type or category of role associated with Marilyn Monroe in a given context.
-
B.
attendantOf
Indicates that one entity serves as an attendant, helper, or service provider to another entity.
-
C.
designedRole
Indicates that one entity has been created, configured, or intended to serve a particular function, purpose, or role in relation to another entity.
-
D.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
E.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
- F. None of above. chosen
Provenance (4 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af07078cb081909f64326b12522410 |
completed | March 9, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69af019155448190b19868583272513f |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af07059d288190a1ea79449414fbce |
completed | March 9, 2026, 5:44 p.m. |
Created at: March 9, 2026, 3:45 p.m.