Triple
T23303397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon Airport |
E590366
|
entity |
| Predicate | IATA code |
P2569
|
FINISHED |
| Object | SNN |
—
|
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: SNN | Statement: [Shannon Airport, IATA code, SNN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SNN Context triple: [Shannon Airport, IATA code, SNN]
-
A.
SNN
SNN is the National Rail station code assigned to Swinton railway station in South Yorkshire, England.
-
B.
SNN
chosen
SNN is the three-letter IATA airport code for Shannon Airport in County Clare, Ireland, a major international gateway on the country’s west coast.
-
C.
SSNNL
SSNNL is a Gujarat government-owned corporation responsible for implementing and managing the Sardar Sarovar dam and related Narmada river irrigation and power projects.
-
D.
Neuron
Neuron is a leading peer-reviewed scientific journal that publishes influential research in neuroscience, covering topics from molecular and cellular mechanisms to systems and cognitive neuroscience.
-
E.
BNNS
BNNS (Basic Neural Network Subroutines) is Apple’s low-level, hardware-accelerated framework for performing neural network and machine learning computations efficiently on Apple devices.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19724de488190ac8eb89253c8dd53 |
completed | April 29, 2026, 5:29 a.m. |
Created at: April 17, 2026, 5:04 p.m.