Triple
T30510849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Right to Remain Silent |
E776415
|
entity |
| Predicate | showsExpertiseOf |
P106039
|
FINISHED |
| Object | Charles Brandt |
—
|
NE NERFINISHED |
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: Charles Brandt | Statement: [The Right to Remain Silent, showsExpertiseOf, Charles Brandt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showsExpertiseOf Context triple: [The Right to Remain Silent, showsExpertiseOf, Charles Brandt]
-
A.
skilledIn
Indicates that an entity possesses ability, expertise, or proficiency in performing or using another entity (such as a task, tool, or domain).
-
B.
basedOnExpertiseOf
chosen
Indicates that something is determined, derived, or justified using the knowledge, skills, or judgment of a particular expert or group of experts.
-
C.
indicatesSkill
Indicates a relationship where one entity possesses, demonstrates, or is associated with a particular skill represented by another entity.
-
D.
usesKnowledgeOf
Indicates that one entity applies or draws upon the knowledge possessed by another entity in performing an action or achieving a result.
-
E.
killsAt
Indicates that one entity causes the death of another entity at a specific time or event.
- 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_69f2249a155c8190b1d512106007e9bb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 8:16 p.m.