Triple
T24759380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curt Cress |
E619388
|
entity |
| Predicate | hasWorkedWith |
P9615
|
FINISHED |
| Object |
Milli Vanilli
Milli Vanilli was a late-1980s German-French R&B/pop duo best known for their commercial success and subsequent lip-syncing scandal that led to one of the most infamous controversies in pop music history.
|
E1651277
|
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: Milli Vanilli | Statement: [Curt Cress, hasWorkedWith, Milli Vanilli]
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: Milli Vanilli Triple: [Curt Cress, hasWorkedWith, Milli Vanilli]
Generated description
Milli Vanilli was a late-1980s German-French R&B/pop duo best known for their commercial success and subsequent lip-syncing scandal that led to one of the most infamous controversies in pop music history.
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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f4107b385481908ed34c8c4dc90c45 |
completed | May 1, 2026, 2:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a101c0e293881909ef3f139d0719255 |
completed | May 22, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_6a1024aaf1e48190b70f890bfa9a1ec4 |
completed | May 22, 2026, 9:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1025c5fb188190bd117ec73114af3e |
completed | May 22, 2026, 9:45 a.m. |
Created at: April 18, 2026, 4:27 a.m.