Triple
T7072175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joel Silver |
E164724
|
entity |
| Predicate | notableWork |
P4
|
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: [Joel Silver, notableWork, Ricochet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ricochet Context triple: [Joel Silver, notableWork, 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.
Bounce
"Bounce" is a popular Afrobeats song by Nigerian singer Rema, known for its energetic production and catchy, dance-oriented style.
-
D.
Bounce
"Bounce" is a 2002 hard rock album by Bon Jovi that reflects themes of resilience and renewal, influenced in part by the aftermath of the September 11 attacks.
-
E.
Ossuccio
Ossuccio is a small lakeside locality on the western shore of Lake Como in northern Italy, known for its scenic setting opposite the historic Isola Comacina.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c9cdbc8190b91cd3b4eef58eb6 |
completed | March 27, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7945fdafc81909c265373627af4e8 |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:39 p.m.