Triple
T4014056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madlib |
E90712
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Bandana |
E343484
|
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: Bandana | Statement: [Madlib, notableWork, Bandana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bandana Context triple: [Madlib, notableWork, Bandana]
-
A.
Bandana
chosen
Bandana is a critically acclaimed collaborative hip-hop album by rapper Freddie Gibbs and producer Madlib, known for its intricate lyricism and soulful, sample-heavy production.
-
B.
Bandag
Bandag is a Bridgestone-owned brand best known for its commercial truck tire retreading products and services.
-
C.
Banda
Banda is a city in the Bundelkhand region of Uttar Pradesh, India, known for its historical significance and proximity to the Ken River.
-
D.
Band-Aid
Band-Aid is a widely known brand of adhesive bandages and first-aid products commonly used to cover and protect minor cuts and wounds.
-
E.
La Banda
La Banda is a major city in northern Argentina known for its agricultural economy and proximity to the provincial capital, Santiago del Estero.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8ad6348190b71feaf8c18c90c2 |
completed | March 9, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c73e6048190a59a8d8bc12c907d |
completed | March 14, 2026, 11:54 a.m. |
Created at: March 9, 2026, 3:35 p.m.