Triple
T17967839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harmon |
E449258
|
entity |
| Predicate | notableBearer |
P458
|
FINISHED |
| Object | Mark Harmon |
—
|
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: Mark Harmon | Statement: [Harmon, notableBearer, Mark Harmon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Harmon Context triple: [Harmon, notableBearer, Mark Harmon]
-
A.
Mark Harmon
chosen
Mark Harmon is an American actor best known for his long-running role as Special Agent Leroy Jethro Gibbs on the television series NCIS.
-
B.
Dylan McDermott
Dylan McDermott is an American actor best known for his roles in the legal drama "The Practice" and the anthology series "American Horror Story."
-
C.
Gregg Henry
Gregg Henry is an American character actor and musician known for his prolific work in film and television, often portraying intense or villainous roles.
-
D.
Leo Willis
Leo Willis was an American character actor active during the silent and early sound film eras, often appearing in comedies alongside stars like Harold Lloyd.
-
E.
Dennis Haysbert
Dennis Haysbert is an American actor known for his deep voice and prominent roles in film and television, including "24," "Major League," and numerous commercial campaigns.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b13935908190b5269a84a3df2460 |
completed | April 19, 2026, 10:40 a.m. |
Created at: April 10, 2026, 10:22 a.m.