Triple
T28541880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Book of Basketball 2.0 |
E722310
|
entity |
| Predicate | primaryHostEmployer |
P129978
|
FINISHED |
| Object | The Ringer |
—
|
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: The Ringer | Statement: [The Book of Basketball 2.0, primaryHostEmployer, The Ringer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryHostEmployer Context triple: [The Book of Basketball 2.0, primaryHostEmployer, The Ringer]
-
A.
parentEmployer
Indicates that one organization is the direct or higher-level employer of another organization or entity.
-
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.
employerOrPrimaryClient
chosen
Indicates that one entity serves as the main employer or principal client of another entity in a work or service relationship.
-
D.
employerOrOwnerOf
Indicates that one entity serves as the employer of, or holds ownership over, another entity.
-
E.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_6a004fd3caf48190b2ec063a7bf0756b |
completed | May 10, 2026, 9:28 a.m. |
| PD | Predicate disambiguation | batch_6a004f7672dc8190aca91d1ed855bf9a |
completed | May 10, 2026, 9:27 a.m. |
Created at: April 28, 2026, 3:36 a.m.