Triple
T21637148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valve |
E533989
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Ricochet |
—
|
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: Ricochet | Statement: [Valve, notableWork, Ricochet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ricochet Context triple: [Valve, notableWork, Ricochet]
-
A.
Ricochet
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
chosen
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.
Ricochet
Ricochet is a 1975 live album by the German electronic music group Tangerine Dream, known for its atmospheric, improvisational synthesizer soundscapes.
-
E.
"Ricochet"
"Ricochet" is a popular 1953 novelty pop song performed by American singer Teresa Brewer.
- 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef538eef0481908f5bf0e27f8e054d |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 16, 2026, 6:35 p.m.