Triple

T18200431
Position Surface form Disambiguated ID Type / Status
Subject Judea Pearl E435765 entity
Predicate notableConcept P201 FINISHED
Object ladder of causation
The ladder of causation is Judea Pearl’s three-level framework (association, intervention, and counterfactuals) for understanding and formalizing causal reasoning.
E1311835 NE FINISHED

How this triple was built (4 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.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: ladder of causation
Triple: [Judea Pearl, notableConcept, ladder of causation]
Generated description
The ladder of causation is Judea Pearl’s three-level framework (association, intervention, and counterfactuals) for understanding and formalizing causal reasoning.
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 (5 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.
NED1 Entity disambiguation (via context triple) batch_6a03980f600c819099f3fb14744f8afa completed May 12, 2026, 9:13 p.m.
NEDg Description generation batch_6a0398fb7fb481908a32c56a798d81fd completed May 12, 2026, 9:17 p.m.
NED2 Entity disambiguation (via description) batch_6a039a2b85888190bbcae1ba9d8ba715 completed May 12, 2026, 9:22 p.m.
Created at: April 10, 2026, 10:31 a.m.