Triple
T29582127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Torrance about the hotel’s history |
E753615
|
entity |
| Predicate | audienceKnowledgeType |
P134335
|
FINISHED |
| Object | diegeticInformation |
—
|
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: diegeticInformation | Statement: [Jack Torrance about the hotel’s history, audienceKnowledgeType, diegeticInformation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audienceKnowledgeType Context triple: [Jack Torrance about the hotel’s history, audienceKnowledgeType, diegeticInformation]
-
A.
targetAudienceKnowledge
chosen
Indicates the level or type of prior knowledge that the intended audience is expected to have.
-
B.
knowledgeType
Indicates the specific category or nature of knowledge associated with an entity or statement (e.g., factual, procedural, conceptual).
-
C.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
D.
knowledgeScope
Indicates the extent or range of information, topics, or understanding that an entity possesses or is concerned with.
-
E.
dramaticKnowledgeLevel
Indicates the extent or degree to which an entity possesses knowledge or understanding specifically related to drama or theatrical arts.
- 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_69f0ef80bf8c8190ad286e99f7df0c63 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66d7b547c8190ba4bfef5c7567a77 |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:07 p.m.