Triple
T12658964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Congdon |
E302363
|
entity |
| Predicate | subjectOfWorkMissRepresentation |
P7040
|
FINISHED |
| Object | portrayal of women in the media |
—
|
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: portrayal of women in the media | Statement: [Jessica Congdon, subjectOfWorkMissRepresentation, portrayal of women in the media]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectOfWorkMissRepresentation Context triple: [Jessica Congdon, subjectOfWorkMissRepresentation, portrayal of women in the media]
-
A.
subjectOfWork
chosen
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
-
B.
neverRepresentedBy
Indicates that one entity has at no time been represented or acted on behalf of by the other entity.
-
C.
missingOrgan
Indicates that an entity lacks or no longer possesses a specific organ that would normally be present.
-
D.
misrepresentedAs
Indicates that one entity is falsely or inaccurately presented, portrayed, or described as another entity or in another way.
-
E.
workRepresented
Indicates that one entity is a representation (such as a depiction, adaptation, or portrayal) of another work.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:19 p.m.