Triple
T32329531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jon Secada |
E826008
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Too Late, Too Soon
"Too Late, Too Soon" is a pop ballad by Cuban-American singer Jon Secada, released in the mid-1990s and known for its soulful vocals and romantic theme.
|
E2002582
|
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: Too Late, Too Soon | Statement: [Jon Secada, notableWork, Too Late, Too Soon]
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: Too Late, Too Soon Triple: [Jon Secada, notableWork, Too Late, Too Soon]
Generated description
"Too Late, Too Soon" is a pop ballad by Cuban-American singer Jon Secada, released in the mid-1990s and known for its soulful vocals and romantic theme.
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_69f34913d9048190befaa634025232be |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bdec99648190824bce6e87d70be6 |
completed | May 3, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3057242d6081909be790ac6516706e |
completed | June 15, 2026, 7:48 p.m. |
| NEDg | Description generation | batch_6a31b300d77481909c984dc72bd43896 |
completed | June 16, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a31b35858908190a7ebbe3bea7d8ce3 |
completed | June 16, 2026, 8:34 p.m. |
Created at: May 1, 2026, 12:47 a.m.