Triple
T4146612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Robot |
E89798
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Tyrell Wellick |
E387495
|
NE 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: Tyrell Wellick | Statement: [Mr. Robot, featuresCharacter, Tyrell Wellick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tyrell Wellick Context triple: [Mr. Robot, featuresCharacter, Tyrell Wellick]
-
A.
Tyrell Wellick
chosen
Tyrell Wellick is a high-ranking, ambitious executive at E Corp who becomes deeply entangled in Elliot Alderson’s hacking schemes and psychological conflicts in the TV series "Mr. Robot."
-
B.
Taryll Jackson
Taryll Jackson is an American singer, songwriter, and member of the R&B group 3T, known for being part of the musical Jackson family.
-
C.
Isaiah Rogers
Isaiah Rogers was a prominent 19th-century American architect known for pioneering hotel design and contributing major public buildings in the United States.
-
D.
Ezekiel Jones
Ezekiel Jones is a charming, tech-savvy master thief and one of the main Librarians in the fantasy adventure TV series "The Librarians."
-
E.
Trey Wilson
Trey Wilson was an American character actor best known for his memorable supporting roles in 1980s films such as "Bull Durham" and "Raising Arizona."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed95a59a881909b26e70b42c6811a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af025fef088190b42515d0a854a1ae |
completed | March 9, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f3136c48190b158142311bfbc6d |
completed | March 14, 2026, 3:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.