Triple
T420567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sacramento International Airport |
E8091
|
entity |
| Predicate | FAAcode |
P420
|
FINISHED |
| Object | SMF |
E53313
|
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: SMF | Statement: [Sacramento International Airport, FAAcode, SMF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SMF Context triple: [Sacramento International Airport, FAAcode, SMF]
-
A.
SMF
chosen
SMF is the three-letter IATA airport code for Sacramento International Airport, the primary commercial airport serving California’s capital city.
-
B.
MFS
MFS (Macintosh File System) is the original flat file system used by early Macintosh computers before the introduction of the hierarchical HFS.
-
C.
SF
SF is the standard two-letter postal abbreviation used to represent the city of San Francisco, California.
-
D.
KSMF
KSMF is the ICAO airport code for Sacramento International Airport, a major commercial airport serving California’s capital region.
-
E.
SIM
SIM is the commonly used abbreviation for the Science and Industry Museum in Manchester, a major UK museum dedicated to the history and impact of science, technology, and industry.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebf65cc81908196fee4f09d5889 |
completed | Feb. 28, 2026, 1:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a42a15efe88190b1dc3337bd775723 |
completed | March 1, 2026, 11:59 a.m. |
Created at: Feb. 28, 2026, 1:11 p.m.