Triple
T15033609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony |
E378419
|
entity |
| Predicate | portrayedInImaginariumSequencesBy |
P9616
|
FINISHED |
| Object | Jude Law |
E29731
|
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: Jude Law | Statement: [Tony, portrayedInImaginariumSequencesBy, Jude Law]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jude Law Context triple: [Tony, portrayedInImaginariumSequencesBy, Jude Law]
-
A.
Jude Law
chosen
Jude Law is an English actor known for his versatile performances in films such as "The Talented Mr. Ripley," "Cold Mountain," and the "Sherlock Holmes" series.
-
B.
Jack Davenport
Jack Davenport is a British actor best known for his roles in the television series "Coupling" and the "Pirates of the Caribbean" film franchise.
-
C.
Matthew Goode
Matthew Goode is an English actor known for his roles in films such as "Match Point," "The Imitation Game," and "Stoker," as well as TV series like "Downton Abbey" and "The Good Wife."
-
D.
Clive Owen
Clive Owen is an English actor known for his intense, brooding screen presence in films such as "Closer," "Children of Men," and "Inside Man."
-
E.
Dominic Cooper
Dominic Cooper is an English actor known for his roles in films such as "Mamma Mia!" and "The Devil's Double," as well as the TV series "Preacher."
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e3a7c8819081f26c2435c1bcb2 |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5b4d58481908afbc89263e07b50 |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 2:59 a.m.