Triple
T24367304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reticence in Literature |
E614230
|
entity |
| Predicate | critiquesTrend |
P82153
|
FINISHED |
| Object | emerging tendencies toward frankness in English writing |
—
|
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: emerging tendencies toward frankness in English writing | Statement: [Reticence in Literature, critiquesTrend, emerging tendencies toward frankness in English writing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: critiquesTrend Context triple: [Reticence in Literature, critiquesTrend, emerging tendencies toward frankness in English writing]
-
A.
trends
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
-
B.
critiquesConcept
Indicates that one entity analyzes, evaluates, or challenges the ideas or principles represented by another entity.
-
C.
critiquesAspect
chosen
Indicates that one entity evaluates and expresses critical judgment about a particular aspect or component of another entity.
-
D.
aimsToCritique
Indicates an intention to analyze and point out faults, limitations, or weaknesses in something.
-
E.
usedToCritique
Indicates that something is employed as a means to analyze, evaluate, or express disapproval of something else.
- 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_69e2d7e1e010819098b95eb3f905943d |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29388c9308190a7a70bf75ed1501c |
completed | April 29, 2026, 11:26 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:01 a.m.