Triple
T4053619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book 2: Of the Passions |
E84641
|
entity |
| Predicate | examinesRelationBetween |
P12753
|
FINISHED |
| Object | passion and action |
—
|
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: passion and action | Statement: [Book 2: Of the Passions, examinesRelationBetween, passion and action]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: examinesRelationBetween Context triple: [Book 2: Of the Passions, examinesRelationBetween, passion and action]
-
A.
valueRelation
Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
-
B.
semanticRelation
chosen
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
C.
definesRelationshipBetween
Indicates that one entity specifies or establishes the nature, type, or rules of a relationship that exists between two or more other entities.
-
D.
titleRelation
Indicates a relationship where one entity serves as the title, designation, or formal name associated with another entity.
-
E.
bilateralRelation
Indicates a mutual or two-way relationship between two entities, where each affects or interacts with the other.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefba878a48190a2e234d775215938 |
completed | March 9, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.