Triple
T26989144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Cunanan |
E679817
|
entity |
| Predicate | mediaDepictionType |
P17824
|
FINISHED |
| Object | television miniseries |
—
|
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 miniseries | Statement: [Andrew Cunanan, mediaDepictionType, television miniseries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaDepictionType Context triple: [Andrew Cunanan, mediaDepictionType, television miniseries]
-
A.
mediaDepictionAs
chosen
Indicates that one entity is portrayed or represented as another entity or in a particular way within some medium (e.g., image, film, text).
-
B.
mediaReferenceType
Indicates the specific kind of relationship or role that a referenced media item has in relation to another entity or context.
-
C.
mediaType
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
D.
mediaAspect
Indicates the specific aspect ratio or dimensional proportion of a media item in relation to its width and height.
-
E.
mediaTypeOfShow
Indicates the relationship between a show and the type of media format in which it is presented (e.g., TV, radio, streaming).
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c663be481908f233d25d28713a4 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 6:50 a.m.