Triple
T38656465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Moffitt |
E939903
|
entity |
| Predicate | mediaTypeDirected |
P148027
|
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 Moffitt, mediaTypeDirected, television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaTypeDirected Context triple: [John Moffitt, mediaTypeDirected, television]
-
A.
mediaType
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
B.
directedMedium
chosen
Indicates that an action or communication was directed or transmitted through a particular medium or channel.
-
C.
mediaTypeOrigin
Indicates the original source or context from which a particular media type was derived or introduced.
-
D.
mediaDirection
Indicates the direction or flow of media transmission between entities, such as who is sending and who is receiving the media.
-
E.
mediaTypeExample
Indicates that something serves as an example or illustrative instance of a particular media type.
- 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_69f76ede49648190a48bfe47032a05a3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.