Triple
T12108584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Inquirer |
E288364
|
entity |
| Predicate | editorialStanceInFiction |
P8702
|
FINISHED |
| Object | sensationalist |
—
|
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: sensationalist | Statement: [New York Inquirer, editorialStanceInFiction, sensationalist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: editorialStanceInFiction Context triple: [New York Inquirer, editorialStanceInFiction, sensationalist]
-
A.
editorialStance
chosen
Indicates the position, viewpoint, or bias an editor or publication adopts toward a subject, issue, or entity.
-
B.
hasAuthorialStance
Indicates that an entity expresses, embodies, or is associated with a particular author’s viewpoint, attitude, or perspective toward its subject matter.
-
C.
positionInFiction
Indicates that one entity holds a specific role, status, or placement within a fictional work or narrative.
-
D.
literaryPurpose
Indicates the intended function, effect, or communicative goal that a text or passage is meant to achieve within a literary context.
-
E.
qualityInFiction
Indicates that a particular quality, trait, or characteristic is exhibited by an entity within a fictional context or 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.