Triple
T37056989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Dragon |
E917217
|
entity |
| Predicate | hasRelease |
P22087
|
FINISHED |
| Object |
Slugs of Love
Slugs of Love is a studio album by Swedish electronic music band Little Dragon, showcasing their blend of synth-pop, R&B, and experimental sounds.
|
E2210427
|
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: Slugs of Love | Statement: [Little Dragon, hasRelease, Slugs of Love]
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: Slugs of Love Triple: [Little Dragon, hasRelease, Slugs of Love]
Generated description
Slugs of Love is a studio album by Swedish electronic music band Little Dragon, showcasing their blend of synth-pop, R&B, and experimental sounds.
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_69f76e94d0308190a3f06890e133c88e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb2f6a28588190931da28eb143e61d |
completed | May 6, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3e8c51bc1c819096a82727dc790f6e |
completed | June 26, 2026, 2:27 p.m. |
| NEDg | Description generation | batch_6a3e98307d6481908425944dcd45d32a |
completed | June 26, 2026, 3:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3ea36c66788190a0be0d0f84c1090b |
completed | June 26, 2026, 4:06 p.m. |
Created at: May 3, 2026, 4:14 p.m.