Triple
T4509874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Herron |
E102022
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mark Herron |
E102022
|
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: Mark Herron | Statement: [Mark Herron, name, Mark Herron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Herron Context triple: [Mark Herron, name, Mark Herron]
-
A.
Mark Herron
chosen
Mark Herron was an American actor best known for being the fourth husband of legendary entertainer Judy Garland.
-
B.
Matt Hulett
Matt Hulett is an American technology and business executive known for leading and scaling multiple software and digital media companies.
-
C.
Tim Haines
Tim Haines is a British television producer and director best known for creating groundbreaking prehistoric and natural history series that blend documentary storytelling with cutting-edge visual effects.
-
D.
Darren Morfitt
Darren Morfitt is a British actor known for his roles in television dramas and genre series, including appearances in Doctor Who.
-
E.
Curt Henderson
Curt Henderson is a central character from the coming-of-age film "American Graffiti," portrayed as a thoughtful, somewhat restless teenager on the brink of leaving his small town for college.
- 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_69bd43d6251c81909deecce3e6e9d69c |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd571138b88190b68bbfc4300aaf9d |
completed | March 20, 2026, 2:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4d66d4948190a095a92d0e3778ca |
completed | March 21, 2026, 7:48 a.m. |
Created at: March 20, 2026, 1:01 p.m.