Triple
T24988571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Broadway Nitelites |
E625385
|
entity |
| Predicate | associatedWithLabel |
P51475
|
FINISHED |
| Object |
Clarion Records
Clarion Records is a record label known for releasing music by artists such as The Broadway Nitelites.
|
E1697850
|
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: Clarion Records | Statement: [The Broadway Nitelites, associatedWithLabel, Clarion Records]
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: Clarion Records Triple: [The Broadway Nitelites, associatedWithLabel, Clarion Records]
Generated description
Clarion Records is a record label known for releasing music by artists such as The Broadway Nitelites.
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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44a42f61c8190bcb01ceec1f889b1 |
completed | May 1, 2026, 6:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a10d9dc70748190b9f10aa68fde4056 |
completed | May 22, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_6a10dba011fc81908d42063a1c2e7714 |
completed | May 22, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a10dc2096b881909e87c9cc277bc831 |
completed | May 22, 2026, 10:43 p.m. |
Created at: April 18, 2026, 6:03 a.m.