Triple
T25157820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dresden Dolls |
E626362
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object |
Coin-Operated Boy
"Coin-Operated Boy" is a darkly whimsical cabaret-rock song by The Dresden Dolls that explores themes of artificial love and emotional detachment.
|
E1669044
|
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: Coin-Operated Boy | Statement: [The Dresden Dolls, notableSong, Coin-Operated Boy]
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: Coin-Operated Boy Triple: [The Dresden Dolls, notableSong, Coin-Operated Boy]
Generated description
"Coin-Operated Boy" is a darkly whimsical cabaret-rock song by The Dresden Dolls that explores themes of artificial love and emotional detachment.
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_69e2ff2834ec8190b0872e2ec3d76023 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f46b8a2dcc81908fc6d9f01dbb2c63 |
completed | May 1, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a105d0e0974819083e97eaf0f4c5a39 |
completed | May 22, 2026, 1:41 p.m. |
| NEDg | Description generation | batch_6a105dd12cd08190b382c57952107fa6 |
completed | May 22, 2026, 1:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a105ed31dd481908a09f91fcb860641 |
completed | May 22, 2026, 1:49 p.m. |
Created at: April 18, 2026, 6:30 a.m.