Triple
T11996328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Bettis |
E285538
|
entity |
| Predicate | hasWrittenForMedium |
P85369
|
FINISHED |
| Object | television |
—
|
LITERAL FINISHED |
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: television | Statement: [John Bettis, hasWrittenForMedium, television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWrittenForMedium Context triple: [John Bettis, hasWrittenForMedium, television]
-
A.
hasWrittenFor
Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
-
B.
hasPublicationMedium
chosen
Indicates the medium or channel through which a work or publication is disseminated or made available.
-
C.
hasWrittenAbout
Indicates that one entity has authored content or material discussing, analyzing, or referencing another entity.
-
D.
isWritten
Indicates that a text, document, or content has been created or recorded in written form by an agent.
-
E.
hasWrittenNonFiction
Indicates that a person is the author of one or more non-fiction works.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.