Triple

T17587947
Position Surface form Disambiguated ID Type / Status
Subject Sample Selection Bias as a Specification Error E428372 entity
Predicate citedFor P9877 FINISHED
Object Heckman correction — NE NERFINISHED

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: Heckman correction | Statement: [Sample Selection Bias as a Specification Error, citedFor, Heckman correction]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Heckman correction
Context triple: [Sample Selection Bias as a Specification Error, citedFor, Heckman correction]
  • A. Heckman correction chosen
    The Heckman correction is an econometric technique that adjusts for sample selection bias in regression models by jointly modeling the selection process and the outcome.
  • B. Heckman selection model
    The Heckman selection model is an econometric technique that corrects for sample selection bias in regression analysis by jointly modeling the selection process and the outcome equation.
  • C. Frisch–Waugh–Lovell theorem
    The Frisch–Waugh–Lovell theorem is a fundamental result in econometrics that shows how the coefficients of a multiple linear regression can be obtained by first partialling out (regressing out) other explanatory variables.
  • D. “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.
  • E. LIML
    LIML is the ICAO airport code for Milan Linate Airport, a major city airport serving Milan, Italy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469e41bf08190963848f1597b6e9f completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 5:51 a.m.