Triple
T20288943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagpur Airport |
E509964
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object | NAG |
—
|
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: NAG | Statement: [Nagpur Airport, IATAcode, NAG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NAG Context triple: [Nagpur Airport, IATAcode, NAG]
-
A.
NAG
chosen
NAG is the IATA airport code for Dr. Babasaheb Ambedkar International Airport serving Nagpur, India.
-
B.
NAG Library
NAG Library is a comprehensive, commercially developed numerical software library providing a wide range of routines for mathematical and statistical computation.
-
C.
NAP
NAP is the IATA airport code for Naples International Airport, the main air gateway serving the city of Naples in southern Italy.
-
D.
NAP
NAP is the publishing arm of the U.S. National Academies that produces and disseminates authoritative reports on science, engineering, and medicine.
-
E.
NAO
NAO is a large-scale atmospheric pressure pattern over the North Atlantic that strongly influences weather and climate variability in Europe, North America, and surrounding regions.
- 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e67694d50881909d59c1037295c1d0 |
completed | April 20, 2026, 6:55 p.m. |
Created at: April 16, 2026, 11:10 a.m.