Triple
T15878979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald B. Rubin |
E385023
|
entity |
| Predicate | notableConcept |
P201
|
FINISHED |
| Object |
multiple imputation for nonresponse in surveys
Multiple imputation for nonresponse in surveys is a statistical methodology that replaces missing survey data with multiple sets of plausible values to allow valid inference that accounts for uncertainty due to nonresponse.
|
E1181898
|
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: multiple imputation for nonresponse in surveys | Statement: [Donald B. Rubin, notableConcept, multiple imputation for nonresponse in surveys]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: multiple imputation for nonresponse in surveys Context triple: [Donald B. Rubin, notableConcept, multiple imputation for nonresponse in surveys]
-
A.
Statistics Surveys
Statistics Surveys is an open-access, peer-reviewed journal that publishes survey and review articles covering a broad range of topics in statistics and probability.
-
B.
A Solution to the Ecological Inference Problem
A Solution to the Ecological Inference Problem is a influential methodological book by political scientist Gary King that introduces statistical techniques for inferring individual-level behavior from aggregate data.
-
C.
Fundamental Principles of Official Statistics
The Fundamental Principles of Official Statistics are a set of internationally agreed guidelines that define the professional and ethical standards for producing reliable, impartial, and high-quality official statistics.
-
D.
“Statistical Confluence Analysis by Means of Complete Regression Systems”
“Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
-
E.
“Sample Selection Bias as a Specification Error”
“Sample Selection Bias as a Specification Error” is a landmark econometrics paper by James Heckman that introduced the Heckman correction for dealing with non-randomly selected samples in statistical analysis.
- 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: multiple imputation for nonresponse in surveys Triple: [Donald B. Rubin, notableConcept, multiple imputation for nonresponse in surveys]
Generated description
Multiple imputation for nonresponse in surveys is a statistical methodology that replaces missing survey data with multiple sets of plausible values to allow valid inference that accounts for uncertainty due to nonresponse.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: multiple imputation for nonresponse in surveys Target entity description: Multiple imputation for nonresponse in surveys is a statistical methodology that replaces missing survey data with multiple sets of plausible values to allow valid inference that accounts for uncertainty due to nonresponse.
-
A.
Statistics Surveys
Statistics Surveys is an open-access, peer-reviewed journal that publishes survey and review articles covering a broad range of topics in statistics and probability.
-
B.
A Solution to the Ecological Inference Problem
A Solution to the Ecological Inference Problem is a influential methodological book by political scientist Gary King that introduces statistical techniques for inferring individual-level behavior from aggregate data.
-
C.
Fundamental Principles of Official Statistics
The Fundamental Principles of Official Statistics are a set of internationally agreed guidelines that define the professional and ethical standards for producing reliable, impartial, and high-quality official statistics.
-
D.
“Statistical Confluence Analysis by Means of Complete Regression Systems”
“Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
-
E.
“Sample Selection Bias as a Specification Error”
“Sample Selection Bias as a Specification Error” is a landmark econometrics paper by James Heckman that introduced the Heckman correction for dealing with non-randomly selected samples in statistical analysis.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e155ff96588190b8fca1c3bf4a39a2 |
completed | April 16, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9529ac48190993d1af234faea3b |
completed | May 9, 2026, 9:38 p.m. |
| NEDg | Description generation | batch_69ffa9e9b17c8190b98d930fd5cb0723 |
completed | May 9, 2026, 9:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffaa973274819080889e1b9883b8dc |
completed | May 9, 2026, 9:43 p.m. |
Created at: April 10, 2026, 4:51 a.m.