Triple
T6823119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Human Condition |
E156947
|
entity |
| Predicate | setsInContrast |
P40635
|
FINISHED |
| Object | vita activa |
—
|
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: vita activa | Statement: [The Human Condition, setsInContrast, vita activa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setsInContrast Context triple: [The Human Condition, setsInContrast, vita activa]
-
A.
setsIn
Indicates that one entity places or positions another entity into or within a specified container, location, or context.
-
B.
createsContrastIn
chosen
Indicates a relationship where one element is used to highlight or emphasize differences with another element within a given context.
-
C.
comparisonSet
Indicates that one entity is part of a group of entities that are being compared or evaluated against each other.
-
D.
setsOut
Indicates that an entity begins a journey, course of action, or process, moving from an initial state or location toward a goal or destination.
-
E.
exploresContrastBetween
Indicates a relationship in which one entity examines, highlights, or analyzes the differences or oppositions between two or more entities, ideas, or situations.
- 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_69c688298a288190af3f285d57f76bbe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d57f69cc8190bbd08a8d447e616f |
completed | March 27, 2026, 7:07 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:17 p.m.