Triple
T20652649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morgan Mason |
E507536
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Morgan Mason |
—
|
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: Morgan Mason | Statement: [Morgan Mason, name, Morgan Mason]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morgan Mason Context triple: [Morgan Mason, name, Morgan Mason]
-
A.
Morgan Mason
chosen
Morgan Mason is a British-born film producer and former political operative known for his work in the entertainment industry and his involvement in U.S. Republican politics.
-
B.
Morgan Jones
Morgan Jones is a central survivor and moral compass figure in the post-apocalyptic TV series Fear the Walking Dead, known for his complex journey from trauma and isolation to leadership and hope.
-
C.
Morgan Giles
Morgan Giles is a musician best known as a member of the punk/indie rock band The Underground Railroad to Candyland.
-
D.
Morgan York
Morgan York is an American former child actress best known for her roles in family films and the Disney Channel series "Hannah Montana."
-
E.
Morgan Hart
Morgan Hart is an American actress best known for her work in television and for being married to actor Don Most.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af22d6bc8190b9d6877aba5704eb |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.