Triple
T2508478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Russell |
E52642
|
entity |
| Predicate | mediaUsed |
P33573
|
FINISHED |
| Object | black-and-white photography |
—
|
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: black-and-white photography | Statement: [Lee Russell, mediaUsed, black-and-white photography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaUsed Context triple: [Lee Russell, mediaUsed, black-and-white photography]
-
A.
mediaUse
chosen
Indicates that an entity makes use of, consumes, or engages with a particular medium or media resource.
-
B.
mediaExposure
Indicates the extent to which an entity is subjected to or receives attention from media channels such as television, radio, print, or online platforms.
-
C.
usedByMedia
Indicates that something is employed or utilized by media organizations or media-related channels.
-
D.
mediaMoment
Indicates a specific point or segment within a media item (such as a video, audio, or broadcast) where a notable event or action occurs.
-
E.
mediaWork
Indicates a relationship where one entity is a media-related work (such as a film, book, recording, or other creative media production) associated with another entity.
- 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.