Triple
T34965125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Discoveries |
E1008370
|
entity |
| Predicate | writingApproach |
P175871
|
FINISHED |
| Object | narrative nonfiction |
—
|
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: narrative nonfiction | Statement: [Great Discoveries, writingApproach, narrative nonfiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingApproach Context triple: [Great Discoveries, writingApproach, narrative nonfiction]
-
A.
writingMethod
chosen
Indicates the technique or manner in which something is written or recorded.
-
B.
writingModel
Indicates that one entity serves as the writing system, script, or notation model used to represent the language or written content of another entity.
-
C.
writingComponent
Indicates that one entity is a written part or element that contributes to the composition or structure of another entity.
-
D.
writingForm
Indicates the specific script, notation, or written representation used to express a piece of language or content.
-
E.
writingTool
Indicates that one entity serves as a tool or instrument used by another entity for the act of writing.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.