Triple
T26031006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Bourbon, One Scotch, One Beer |
E647429
|
entity |
| Predicate | originalPerformer |
P11499
|
FINISHED |
| Object |
Amos Milburn
Amos Milburn was an influential American rhythm and blues pianist and singer of the 1940s and 1950s, known for his boogie-woogie style and drinking-themed songs that helped shape early rock and roll.
|
E1716491
|
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: Amos Milburn | Statement: [One Bourbon, One Scotch, One Beer, originalPerformer, Amos Milburn]
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: Amos Milburn Triple: [One Bourbon, One Scotch, One Beer, originalPerformer, Amos Milburn]
Generated description
Amos Milburn was an influential American rhythm and blues pianist and singer of the 1940s and 1950s, known for his boogie-woogie style and drinking-themed songs that helped shape early rock and roll.
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_69e77e8b60e88190a3b26c4f0032a2c2 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f605efbc1c81908d1137f310d781ad |
completed | May 2, 2026, 2:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11855a4ca88190be46584287585edf |
completed | May 23, 2026, 10:45 a.m. |
| NEDg | Description generation | batch_6a118930b3308190837af6a5b703c4a5 |
completed | May 23, 2026, 11:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1189dcc1348190b1318d89e9d24fb9 |
completed | May 23, 2026, 11:05 a.m. |
Created at: April 22, 2026, 9:06 a.m.