Triple
T33544607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chucho Valdés |
E859168
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
album "Jazz Batá"
"Jazz Batá" is a pioneering Afro-Cuban jazz album by pianist Chucho Valdés that blends traditional batá drum rhythms with modern jazz improvisation.
|
E2055829
|
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: album "Jazz Batá" | Statement: [Chucho Valdés, notableWork, album "Jazz Batá"]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: album "Jazz Batá" Triple: [Chucho Valdés, notableWork, album "Jazz Batá"]
Generated description
"Jazz Batá" is a pioneering Afro-Cuban jazz album by pianist Chucho Valdés that blends traditional batá drum rhythms with modern jazz improvisation.
Provenance (5 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_69f3497a5be08190a39b12736899e034 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f6e508788190a4f66e92f6a580e5 |
completed | May 3, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a35a68ab5f48190b571f6c49573bf3c |
completed | June 19, 2026, 8:28 p.m. |
| NEDg | Description generation | batch_6a35a70f36888190b600a3b47adbc24f |
completed | June 19, 2026, 8:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a35a7b4ea908190b56ce58460ee569b |
completed | June 19, 2026, 8:33 p.m. |
Created at: May 1, 2026, 1:39 a.m.