Triple
T20232272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Golden Voyage of Sinbad |
E495557
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Roy Watts |
—
|
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: Roy Watts | Statement: [The Golden Voyage of Sinbad, editedBy, Roy Watts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roy Watts Context triple: [The Golden Voyage of Sinbad, editedBy, Roy Watts]
-
A.
Roy Watts
chosen
Roy Watts is an editor known for his work on the British television drama series "Kes."
-
B.
Jim Watts
Jim Watts is a musician best known as a member of the English post-punk band The Fall.
-
C.
Tony Darrow
Tony Darrow is an American actor best known for his supporting roles as mobsters in films and television, particularly in Martin Scorsese’s crime dramas.
-
D.
Stan Watts
Stan Watts is an artist best known for creating cover artwork, including the cover art for the work titled "Escape."
-
E.
Donald Earl Watts
Donald Earl "Slick" Watts is a former American professional basketball player best known as a flashy, headband-wearing point guard for the Seattle SuperSonics in the 1970s.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fddafac819089cef4158f5e0ab5 |
completed | April 20, 2026, 6:26 p.m. |
Created at: April 11, 2026, 11:39 p.m.