Triple
T4869670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allington |
E109054
|
entity |
| Predicate | hasMediaTypeContext |
P131
|
FINISHED |
| Object | prose fiction |
—
|
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: prose fiction | Statement: [Allington, hasMediaTypeContext, prose fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMediaTypeContext Context triple: [Allington, hasMediaTypeContext, prose fiction]
-
A.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
B.
hasMediaEvent
Indicates that an entity is associated with, or participates in, a specific media-related event (such as a broadcast, publication, or coverage instance).
-
C.
mediaType
chosen
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
D.
hasCanonicalContext
Indicates that something is associated with its primary, standard, or officially recognized contextual setting or framework.
-
E.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
- 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_69bd440d96a48190b0c87069adef2af1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c28e56081908ee411ac94c3769e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:27 p.m.