Triple
T7419207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swing Mob |
E171201
|
entity |
| Predicate | roleInCareers |
P65533
|
FINISHED |
| Object | launched the career of Missy Elliott |
—
|
LITERAL 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: launched the career of Missy Elliott | Statement: [Swing Mob, roleInCareers, launched the career of Missy Elliott]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCareers Context triple: [Swing Mob, roleInCareers, launched the career of Missy Elliott]
-
A.
roleInIndustry
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
-
B.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
C.
roleInIndividualLife
chosen
Indicates the specific function, influence, or involvement that one entity has within the personal life or experiences of another entity.
-
D.
employedRole
Indicates that an entity holds or performs a specific role or position within an employment or work context.
-
E.
describesCareerOf
Indicates that one entity provides a description or characterization of the professional career of another entity.
- F. None of above.
Provenance (3 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2e93ffc8190beb5a1d3eb6c5d23 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.