Triple
T15451677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meagan Good |
E371667
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Waist Deep |
E331428
|
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: Waist Deep | Statement: [Meagan Good, notableWork, Waist Deep]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waist Deep Context triple: [Meagan Good, notableWork, Waist Deep]
-
A.
Waist Deep
chosen
Waist Deep is a 2006 action-crime drama film about an ex-convict’s desperate attempt to rescue his kidnapped son amid gang violence in Los Angeles.
-
B.
6 Feet Deep
6 Feet Deep is a pioneering mid-1990s horrorcore hip-hop album by the group Gravediggaz, known for its dark humor, macabre themes, and influential production.
-
C.
Down Below
"Down Below" is a surreal, autobiographical memoir by artist and writer Leonora Carrington recounting her harrowing experiences of mental breakdown and institutionalization during World War II.
-
D.
(Not Just) Knee Deep
"(Not Just) Knee Deep" is a 1979 funk classic by Funkadelic, renowned for its extended groove, influential bassline, and heavy sampling in later hip-hop and dance music.
-
E.
Dig Deep
"Dig Deep" is a song included on the album "Bombshell."
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03efaf82c81908b464e37ce9c159a |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21b3c5a481908057e94fd84f3cfc |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:30 a.m.