Triple
T34083363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waystar Royco |
E874107
|
entity |
| Predicate | hasFictionalTVNetwork |
P125065
|
FINISHED |
| Object | ATN |
—
|
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: ATN | Statement: [Waystar Royco, hasFictionalTVNetwork, ATN]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalTVNetwork Context triple: [Waystar Royco, hasFictionalTVNetwork, ATN]
-
A.
hasFictionalMediaOutlet
chosen
Indicates that an entity is associated with or features a fictional media outlet (such as an invented TV station, newspaper, or network) within its narrative or context.
-
B.
hasFictionalNetworkExecutive
Indicates that an entity is associated with a fictional character who serves as a network executive.
-
C.
hasFictionalSeries
Indicates that one entity is a fictional series that another entity possesses, is associated with, or is the creator/owner of.
-
D.
hasFictionalProductionCompany
Indicates that one entity is associated with or owns a production company that exists only within a fictional context.
-
E.
hasFictionalEstablishmentType
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
- 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_69f349a61d448190b74642f325d3eb7a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff5f5ecc808190b2df364da108ff4c |
completed | May 9, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69ff5b84131c8190bf81d7fb53e934bc |
completed | May 9, 2026, 4:06 p.m. |
Created at: May 1, 2026, 1:52 a.m.