Triple
T3153986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meagan Good |
E65940
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | La'Myia Good |
E331433
|
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: La'Myia Good | Statement: [Meagan Good, relative, La'Myia Good]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La'Myia Good Context triple: [Meagan Good, relative, La'Myia Good]
-
A.
La'Myia Good
chosen
La'Myia Good is an American singer and actress, best known as a member of the R&B group Isyss and for her work in television and film.
-
B.
Myra Finn
Myra Finn was the first wife of renowned American lyricist and musical theatre producer Oscar Hammerstein II.
-
C.
Mya
Mya is a central female character in the romantic comedy film "Think Like a Man," known for following Steve Harvey’s dating advice as she navigates modern relationships.
-
D.
Momo Blake
Momo Blake is a character from the television series "The Humans," contributing to the show's exploration of complex interpersonal relationships and contemporary social themes.
-
E.
Bayta Darell
Bayta Darell is a pivotal character in Isaac Asimov's Foundation series, known for her crucial role in thwarting the Mule's conquest in "Foundation and Empire."
- 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5e7f4688190b477186254f8a572 |
completed | March 8, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235bf4a008190ba6264103a9d67b7 |
completed | March 12, 2026, 3:40 a.m. |
Created at: March 8, 2026, 3:05 p.m.