Triple
T33577906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Self Control |
E860076
|
entity |
| Predicate | hasISRC |
P15290
|
FINISHED |
| Object |
ITB001400123
ITB001400123 is the ISRC (International Standard Recording Code) assigned to the song "Self Control."
|
E2057270
|
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: ITB001400123 | Statement: [Self Control, hasISRC, ITB001400123]
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: ITB001400123 Triple: [Self Control, hasISRC, ITB001400123]
Generated description
ITB001400123 is the ISRC (International Standard Recording Code) assigned to the song "Self Control."
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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f74d7f80819084e105cd1e36dabe |
completed | May 3, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a35afe11ce08190a4d56a86871102cb |
completed | June 19, 2026, 9:08 p.m. |
| NEDg | Description generation | batch_6a35b061507481908719c10ca850a036 |
completed | June 19, 2026, 9:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a35b150fc008190a481ac837ac996c6 |
completed | June 19, 2026, 9:14 p.m. |
Created at: May 1, 2026, 1:40 a.m.