Triple
T17587846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heckman selection model |
E428370
|
entity |
| Predicate | estimationMethod |
P70307
|
FINISHED |
| Object | Heckman two-step estimator |
—
|
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: Heckman two-step estimator | Statement: [Heckman selection model, estimationMethod, Heckman two-step estimator]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heckman two-step estimator Context triple: [Heckman selection model, estimationMethod, Heckman two-step estimator]
-
A.
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.
-
B.
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.
-
C.
Generalized method of moments
The generalized method of moments is an econometric estimation technique that uses sample moments to infer model parameters without requiring full specification of the underlying probability distribution.
-
D.
LIML
LIML is the ICAO airport code for Milan Linate Airport, a major city airport serving Milan, Italy.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimationMethod Context triple: [Heckman selection model, estimationMethod, Heckman two-step estimator]
-
A.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
B.
separatesEstimationOf
Indicates that one entity distinguishes or isolates the estimation or assessment of another entity from other factors or components.
-
C.
estimatedUsing
chosen
Indicates that one entity’s value, state, or outcome is derived by applying an estimation method, model, or procedure based on another entity.
-
D.
reconstructionMethod
Indicates the technique or process used to reconstruct, restore, or rebuild something from its original or fragmented state.
-
E.
interpretationMethod
Indicates the method, technique, or process used to interpret or derive meaning from something.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e469e41bf08190963848f1597b6e9f |
completed | April 19, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:51 a.m.