Triple
T29838118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Global Underground |
E757709
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object |
James Zabiela
James Zabiela is a British DJ and producer renowned for his technically advanced, genre-blending electronic sets and innovative use of DJ technology.
|
E2002316
|
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: James Zabiela | Statement: [Global Underground, featuresArtist, James Zabiela]
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: James Zabiela Triple: [Global Underground, featuresArtist, James Zabiela]
Generated description
James Zabiela is a British DJ and producer renowned for his technically advanced, genre-blending electronic sets and innovative use of DJ technology.
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_69f224593f6c81908785a560fe659f58 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6760847b48190a5f0548f87faf055 |
completed | May 2, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3056da2a608190977e68558fe47aa0 |
completed | June 15, 2026, 7:47 p.m. |
| NEDg | Description generation | batch_6a305855e3c481908413ec32472544f0 |
completed | June 15, 2026, 7:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a30598159b081908170f49c1a7f0517 |
completed | June 15, 2026, 7:58 p.m. |
Created at: April 29, 2026, 5:38 p.m.