Triple
T35527575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Advocate |
E1026711
|
entity |
| Predicate | employerInStoryline |
P93486
|
FINISHED |
| Object | Brock Lesnar (as client) |
—
|
NE NERFINISHED |
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: Brock Lesnar (as client) | Statement: [The Advocate, employerInStoryline, Brock Lesnar (as client)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerInStoryline Context triple: [The Advocate, employerInStoryline, Brock Lesnar (as client)]
-
A.
employerInPlot
chosen
Indicates that one entity serves as the employer of another within the context of a specific plot or storyline.
-
B.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
C.
employerInReality
Indicates that one entity is the actual, real-world employer of another entity, as opposed to a nominal, legal, or assumed employer.
-
D.
employerInUniverse
Indicates that one entity serves as the employer of another within a specified universe, context, or world.
-
E.
employerService
Indicates that one entity provides employment-related services or functions to another entity, typically in the role of an employer.
- 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:04 p.m.