Triple
T17944764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Moyer |
E448674
|
entity |
| Predicate | coStar |
P43875
|
FINISHED |
| Object | Nelsan Ellis |
—
|
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: Nelsan Ellis | Statement: [Stephen Moyer, coStar, Nelsan Ellis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nelsan Ellis Context triple: [Stephen Moyer, coStar, Nelsan Ellis]
-
A.
Nelsan Ellis
chosen
Nelsan Ellis was an American actor best known for his acclaimed role as Lafayette Reynolds on the HBO series "True Blood."
-
B.
Clint Mathis
Clint Mathis is a retired American soccer forward best known for his prolific scoring in Major League Soccer and his role with the U.S. national team, including at the 2002 FIFA World Cup.
-
C.
Dre Ellis
Dre Ellis is the charismatic hip-hop journalist and central protagonist of the romantic comedy film "Brown Sugar," whose lifelong friendship with a music executive evolves into a deeper love story.
-
D.
Dane Witherspoon
Dane Witherspoon was an American actor best known for his roles in daytime soap operas during the 1980s.
-
E.
Dwayne Hicks
Dwayne Hicks is a fictional Colonial Marine corporal and key supporting character in the science fiction film "Aliens."
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad9819a88190ad4ea7d562cf3f28 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 10:21 a.m.