Triple
T2517510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revolutionary Road |
E55445
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | David Harbour |
E68980
|
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: David Harbour | Statement: [Revolutionary Road, starredActor, David Harbour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Harbour Context triple: [Revolutionary Road, starredActor, David Harbour]
-
A.
David Harbour
chosen
David Harbour is an American actor best known for his role as Jim Hopper in the Netflix series "Stranger Things" and for starring in various film and television projects.
-
B.
Joe Keery
Joe Keery is an American actor and musician best known for his role as Steve Harrington in the Netflix series "Stranger Things."
-
C.
Marc Tarpenning
Marc Tarpenning is an American engineer and entrepreneur best known as a co-founder of electric vehicle and clean energy company Tesla, Inc.
-
D.
Joel Kinnaman
Joel Kinnaman is a Swedish-American actor known for roles in films like "The Suicide Squad" and series such as "The Killing" and "Altered Carbon."
-
E.
Sharlto Copley
Sharlto Copley is a South African actor and filmmaker best known for his roles in science fiction films such as "District 9," "Elysium," and "Chappie."
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2111d28819099884a2bec5e0366 |
completed | March 7, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2b9ef8048190bafff3f1853321cb |
completed | March 9, 2026, 8:20 p.m. |
Created at: March 6, 2026, 9:46 p.m.