Triple
T24184124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book II: The Ancient Monk |
E599504
|
entity |
| Predicate | usesAsContrast |
P120686
|
FINISHED |
| Object | modern industrial society |
—
|
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: modern industrial society | Statement: [Book II: The Ancient Monk, usesAsContrast, modern industrial society]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAsContrast Context triple: [Book II: The Ancient Monk, usesAsContrast, modern industrial society]
-
A.
providesContrastWith
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
-
B.
contrastUse
chosen
Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
-
C.
achievesContrast
Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
-
D.
createsContrastIn
Indicates a relationship where one element is used to highlight or emphasize differences with another element within a given context.
-
E.
registerContrast
Indicates that an entity records or establishes a distinction or difference between two or more items or states.
- 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_69e288cca05481908faeb1563711114a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:35 p.m.