Triple
T28896849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Tobias |
E732854
|
entity |
| Predicate | coCreatedFranchiseWith |
P165502
|
FINISHED |
| Object | Ed Boon |
—
|
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: Ed Boon | Statement: [John Tobias, coCreatedFranchiseWith, Ed Boon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coCreatedFranchiseWith Context triple: [John Tobias, coCreatedFranchiseWith, Ed Boon]
-
A.
createdForFranchise
Indicates that something was created specifically to belong to, support, or be used within a particular franchise.
-
B.
createdFranchise
Indicates that one entity is the originator or founder of a franchise associated with another entity.
-
C.
franchiseCreatorOf
Indicates that an entity is the original creator or originator of a particular franchise.
-
D.
franchiseWorkedOn
Indicates that an entity has contributed work to, or been professionally involved with, a particular franchise.
-
E.
createdByFranchise
Indicates that something (such as a work, product, or entity) was produced or brought into existence by a particular franchise or franchise brand.
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65aa4ed148190bf84678627fdc598 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f6576487e081908d802f1caf59c423 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f65875030881909007c502b7dcc998 |
completed | May 2, 2026, 8:03 p.m. |
Created at: April 28, 2026, 7:59 a.m.