Triple
T12768207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romeo & Juliet (2013 film) |
E305178
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Douglas Booth |
E529080
|
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: Douglas Booth | Statement: [Romeo & Juliet (2013 film), stars, Douglas Booth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Douglas Booth Context triple: [Romeo & Juliet (2013 film), stars, Douglas Booth]
-
A.
Douglas Booth
chosen
Douglas Booth is an English actor known for his roles in film and television dramas, including literary and period adaptations.
-
B.
Patrick J. Adams
Patrick J. Adams is a Canadian actor best known for starring as brilliant college dropout-turned-law associate Mike Ross on the legal drama series "Suits."
-
C.
Orson Cox
Orson Cox is the son of Scottish actor and physicist-turned-science-communicator Brian Cox.
-
D.
Lewis Pullman
Lewis Pullman is an American actor known for roles in films such as "Top Gun: Maverick," "Bad Times at the El Royale," and "The Strangers: Prey at Night."
-
E.
Jeremy Strong
Jeremy Strong is an American actor best known for his Emmy-winning role as Kendall Roy in the HBO series "Succession" and for his performances in films such as "The Big Short" and "Lincoln."
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df3b2f88190b37b696400178795 |
completed | April 10, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684f750a08190abf6122baa579bc4 |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 9, 2026, 5:28 p.m.