Triple
T17546109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rather Ripped |
E427327
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Reena |
—
|
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: Reena | Statement: [Rather Ripped, hasTrack, Reena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reena Context triple: [Rather Ripped, hasTrack, Reena]
-
A.
Reena
chosen
Reena is a feminine given name used in various cultures, often considered a variant spelling of names like Rina.
-
B.
Leena
Leena is a key supporting character in the science fiction television series "Warehouse 13," known for running the bed-and-breakfast where the agents live and for her empathic connection to artifacts.
-
C.
Sunita
Sunita is the given name of Sunita Williams, the American astronaut and United States Navy officer known for her long-duration spaceflights and spacewalk records.
-
D.
Nubeena
Nubeena is a small coastal town on Tasmania’s Tasman Peninsula known as a local service and tourism hub for the surrounding rural and scenic areas.
-
E.
Meena
Meena is a shy teenage elephant with a powerful singing voice in the animated film "Sing."
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45461643881909b106bafb89253b3 |
completed | April 19, 2026, 4:04 a.m. |
Created at: April 10, 2026, 5:49 a.m.