Triple
T22284039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamia |
E550810
|
entity |
| Predicate | studioAlbum |
P25507
|
FINISHED |
| Object | Tamia |
—
|
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: Tamia | Statement: [Tamia, studioAlbum, Tamia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tamia Context triple: [Tamia, studioAlbum, Tamia]
-
A.
Tamia
chosen
Tamia is a Canadian R&B singer and songwriter known for hits like "So Into You" and "Stranger in My House."
-
B.
Jody Watley
Jody Watley is an American singer, songwriter, and former Shalamar member known for her influential role in 1980s and 1990s R&B, pop, and dance music.
-
C.
Keshia Chanté
Keshia Chanté is a Canadian singer, actress, and television personality known for her R&B music career and prominent hosting roles on music video countdown shows.
-
D.
Deniece Williams
Deniece Williams is an American soul and R&B singer best known for her powerful four-octave range and hits like "Let's Hear It for the Boy."
-
E.
Chonita Coleman
Chonita Coleman is a notable member of the Sista organization, recognized for her contributions and involvement within the group.
- 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_69e11e44d538819097c6b8f333af3352 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15605a8448190906a0ab9ffa4260b |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 16, 2026, 8:40 p.m.