Triple
T32644370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leakee |
E834560
|
entity |
| Predicate | employerDuringUse |
P180904
|
FINISHED |
| Object | WWE |
—
|
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: WWE | Statement: [Leakee, employerDuringUse, WWE]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerDuringUse Context triple: [Leakee, employerDuringUse, WWE]
-
A.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
B.
employedUnder
Indicates that one entity works as an employee under the authority, supervision, or organizational structure of another entity.
-
C.
employerSide
Indicates that the subject participates in or represents the employer’s position, interests, or perspective within an employment relationship or dispute.
-
D.
employedThrough
Indicates that an entity holds a job or work position by means of, or via the arrangement of, another entity (such as an agency, contractor, or intermediary).
-
E.
employerInReality
Indicates that one entity is the actual, real-world employer of another entity, as opposed to a nominal, legal, or assumed employer.
- F. None of above. chosen
Provenance (4 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
| PDg | Predicate description generation | batch_69f75788d40c819083bf2567b3091585 |
completed | May 3, 2026, 2:11 p.m. |
Created at: May 1, 2026, 1:07 a.m.