Triple
T9907539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milan Linate Airport |
E185050
|
entity |
| Predicate | hasICAOcode |
P419
|
FINISHED |
| Object | LIML |
E185051
|
NE FINISHED |
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: LIML | Statement: [Milan Linate Airport, hasICAOcode, LIML]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LIML Context triple: [Milan Linate Airport, hasICAOcode, LIML]
-
A.
LIML
chosen
LIML is the ICAO airport code for Milan Linate Airport, a major city airport serving Milan, Italy.
-
B.
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.
-
C.
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.
-
D.
Heckman correction
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.
-
E.
LIM
LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb50ec61481908f42bd2aa55d9a6e |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20daabd5881908b02da50a640766a |
completed | April 5, 2026, 7:22 a.m. |
Created at: March 30, 2026, 8:41 p.m.