Triple
T8969136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russell Mulcahy |
E214217
|
entity |
| Predicate | directorOf |
P537
|
FINISHED |
| Object | Ricochet |
E371109
|
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: Ricochet | Statement: [Russell Mulcahy, directorOf, Ricochet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ricochet Context triple: [Russell Mulcahy, directorOf, Ricochet]
-
A.
Ricochet
chosen
Ricochet is a 1991 action thriller film in which John Lithgow plays a sadistic criminal seeking revenge on a cop who put him behind bars.
-
B.
Ricochet
Ricochet is a wild mouse–style steel roller coaster known for its sharp turns and sudden drops at the Carowinds amusement park.
-
C.
Ricochet
Ricochet was an early wireless internet service network developed by Metricom that provided mobile, high-speed data access in urban areas before Wi-Fi and modern cellular data became widespread.
-
D.
Bounce
"Bounce" is a popular Afrobeats song by Nigerian singer Rema, known for its energetic production and catchy, dance-oriented style.
-
E.
Bounce
"Bounce" is a popular electro house track by Canadian electronic music duo MSTRKRFT, known for its heavy synths and club-oriented energy.
- 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_69ca839dbf608190a2f5990477115d29 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6765babc8190a4a3b79aa21047c8 |
completed | April 1, 2026, 12:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc95cbc4c8190a3ac582f735eeb35 |
completed | April 3, 2026, 2:06 p.m. |
Created at: March 30, 2026, 7:01 p.m.