Triple
T17443037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bandaranaike International Airport |
E424705
|
entity |
| Predicate | hubFor |
P423
|
FINISHED |
| Object | FitsAir |
—
|
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: FitsAir | Statement: [Bandaranaike International Airport, hubFor, FitsAir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FitsAir Context triple: [Bandaranaike International Airport, hubFor, FitsAir]
-
A.
FitsAir
chosen
FitsAir is a Sri Lankan airline that operates passenger and cargo services, primarily within South Asia and the Middle East.
-
B.
FITS
FITS (Flexible Image Transport System) is a standard digital file format widely used in astronomy for storing, transmitting, and processing scientific images and related data.
-
C.
FIT-A
FIT-A is a subdetector module of the Fast Interaction Trigger system used in high-energy physics experiments to provide rapid detection and timing of particle collisions.
-
D.
Fit Feet
Fit Feet is a component of the Healthy Athletes program that focuses on evaluating and promoting proper foot health and footwear for athletes.
-
E.
/fit/
/fit/ is 4chan’s fitness board, dedicated to discussions about exercise, bodybuilding, weight loss, nutrition, and general physical self-improvement.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff927ec8190995798f569e913ba |
completed | April 19, 2026, 3:46 a.m. |
Created at: April 10, 2026, 5:47 a.m.