Triple
T21454990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KRS-One |
E529317
|
entity |
| Predicate | hasAlias |
P455
|
FINISHED |
| Object | Teacha |
—
|
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: Teacha | Statement: [KRS-One, hasAlias, Teacha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teacha Context triple: [KRS-One, hasAlias, Teacha]
-
A.
Teacha
chosen
Teacha is an alias of KRS-One, the influential American rapper and hip-hop philosopher known for his socially conscious lyrics and role in pioneering the genre.
-
B.
Mestra
Mestra is a figure in Greek mythology, daughter of King Erysichthon, known for being granted the power of shape-shifting by Poseidon.
-
C.
Orsa
Orsa is a small locality and municipality in central Sweden known for its forests, lakes, and traditional Dalarna culture.
-
D.
Keila
Keila is a small town in northern Estonia known for its historic church, scenic Keila River and waterfall, and role as a local administrative and transport hub.
-
E.
Taió
Taió is a municipality in the state of Santa Catarina in southern Brazil, situated in the Vale do Itajaí region and known for its agricultural activities and scenic river landscapes.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d612e081909d00ca59a3621cc9 |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:08 p.m.