Triple
T13941975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | You Want This |
E335277
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | MC Lyte |
E120433
|
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: MC Lyte | Statement: [You Want This, featuresArtist, MC Lyte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MC Lyte Context triple: [You Want This, featuresArtist, MC Lyte]
-
A.
MC Lyte
chosen
MC Lyte is a pioneering American rapper and one of the first prominent female MCs in hip-hop, known for her sharp lyricism and influential role in shaping the genre.
-
B.
Roxanne Shanté
Roxanne Shanté is an American hip hop pioneer and battle rapper best known as a founding member of the Juice Crew and one of the first prominent female MCs in rap.
-
C.
Courtney Rose
Courtney Rose is the idealistic young rapper-turned-politician who becomes mayor in the television series "The Mayor."
-
D.
Meshell Ndegeocello
Meshell Ndegeocello is an American singer-songwriter, bassist, and producer known for her genre-blending work in neo-soul, jazz, funk, and R&B.
-
E.
San Monique
San Monique is a fictional Caribbean island nation in the James Bond universe, prominently featured as Dr. Kananga’s stronghold in the film "Live and Let Die."
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf6e29881908ddb8efca9a456a3 |
completed | April 14, 2026, 12:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce8bbd8c819084703298ed6d9c87 |
completed | May 3, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:17 p.m.