Triple
T17229080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Stuart Mill as logician |
E418195
|
entity |
| Predicate | positionOnCausation |
P19804
|
FINISHED |
| Object | causal laws as regularities of succession |
—
|
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: causal laws as regularities of succession | Statement: [John Stuart Mill as logician, positionOnCausation, causal laws as regularities of succession]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnCausation Context triple: [John Stuart Mill as logician, positionOnCausation, causal laws as regularities of succession]
-
A.
positionOnReason
Indicates that one entity holds a particular stance, justification, or rationale concerning another entity or issue.
-
B.
positionOnIssue
Indicates the stance or viewpoint an entity holds regarding a specific issue or topic.
-
C.
positionOnCrime
Indicates a stance, opinion, or policy position that an entity holds regarding crime or crime-related issues.
-
D.
positionOnTruth
Indicates the stance or viewpoint an entity holds regarding the truth or falsity of a given claim or proposition.
-
E.
viewOnCausality
chosen
Indicates a relationship where an entity expresses or embodies a particular perspective or stance on the nature of causality.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42df55e788190b442ffd4fac768c9 |
completed | April 19, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69e3832553ac819091aa917c84f755b6 |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.