Triple
T18200431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judea Pearl |
E435765
|
entity |
| Predicate | notableConcept |
P201
|
FINISHED |
| Object | ladder of causation |
—
|
NE NERFINISHED |
How this triple was built (3 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: ladder of causation | Statement: [Judea Pearl, notableConcept, ladder of causation]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ladder of causation Context triple: [Judea Pearl, notableConcept, ladder of causation]
-
A.
Rubin causal model
The Rubin causal model is a foundational framework in statistics and causal inference that defines causal effects through comparisons of potential outcomes under different treatments or interventions.
-
B.
Funnel of causality
The funnel of causality is a political science model that explains how broad, long-term social and psychological factors gradually narrow to shape an individual’s specific voting decision.
-
C.
Causation
Causation is a central philosophical concept and topic in metaphysics and philosophy of science that examines how and why events bring about or produce other events.
-
D.
Causal Inference for Statistics, Social, and Biomedical Sciences
"Causal Inference for Statistics, Social, and Biomedical Sciences" is a foundational textbook that systematically develops modern methods for drawing causal conclusions from data in fields such as statistics, social science, and biomedicine.
-
E.
The Nomological Character of Causality
The Nomological Character of Causality is a philosophical section that analyzes how causal relations are grounded in, and constrained by, lawlike regularities in nature.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ladder of causation Target entity description: The ladder of causation is Judea Pearl’s three-level framework (association, intervention, and counterfactuals) for understanding and formalizing causal reasoning.
-
A.
Rubin causal model
The Rubin causal model is a foundational framework in statistics and causal inference that defines causal effects through comparisons of potential outcomes under different treatments or interventions.
-
B.
Funnel of causality
The funnel of causality is a political science model that explains how broad, long-term social and psychological factors gradually narrow to shape an individual’s specific voting decision.
-
C.
Causation
Causation is a central philosophical concept and topic in metaphysics and philosophy of science that examines how and why events bring about or produce other events.
-
D.
Causal Inference for Statistics, Social, and Biomedical Sciences
"Causal Inference for Statistics, Social, and Biomedical Sciences" is a foundational textbook that systematically develops modern methods for drawing causal conclusions from data in fields such as statistics, social science, and biomedicine.
-
E.
The Nomological Character of Causality
The Nomological Character of Causality is a philosophical section that analyzes how causal relations are grounded in, and constrained by, lawlike regularities in nature.
- F. None of above. chosen
Provenance (2 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d610f88190b4f69b1c433ea6b1 |
completed | April 19, 2026, 2:04 p.m. |
Created at: April 10, 2026, 10:31 a.m.