Triple
T35768745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stewart Levine |
E1034098
|
entity |
| Predicate | producedAlbum |
P60230
|
FINISHED |
| Object |
Rhapsodies for Young Lovers
Rhapsodies for Young Lovers is a romantic easy-listening album known for its lush orchestral arrangements and mellow, sentimental mood.
|
E2155126
|
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: Rhapsodies for Young Lovers | Statement: [Stewart Levine, producedAlbum, Rhapsodies for Young Lovers]
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: Rhapsodies for Young Lovers Triple: [Stewart Levine, producedAlbum, Rhapsodies for Young Lovers]
Generated description
Rhapsodies for Young Lovers is a romantic easy-listening album known for its lush orchestral arrangements and mellow, sentimental mood.
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_69f76e13edd081909101629aa829c4ad |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a1c9a0888190abc4b26e6f5c4eae |
completed | May 3, 2026, 7:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3885fffdb481908b339b21fd35bddf |
completed | June 22, 2026, 12:46 a.m. |
| NEDg | Description generation | batch_6a3886de289881909bbf9a97aae181d4 |
completed | June 22, 2026, 12:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3887d8cec0819093e671703bfd1fca |
completed | June 22, 2026, 12:54 a.m. |
Created at: May 3, 2026, 4:06 p.m.