Triple
T9050373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tan Son Nhat International Airport |
E216866
|
entity |
| Predicate | hasIATACode |
P2569
|
FINISHED |
| Object | SGN |
E216863
|
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: SGN | Statement: [Tan Son Nhat International Airport, hasIATACode, SGN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SGN Context triple: [Tan Son Nhat International Airport, hasIATACode, SGN]
-
A.
SGN
chosen
SGN is the IATA airport code for Tan Son Nhat International Airport, the main international gateway serving Ho Chi Minh City, Vietnam.
-
B.
SGC
SGC is the station code for St George's Cross, a Glasgow Subway station in Scotland.
-
C.
SG
SG is a postcode area in the United Kingdom covering parts of Hertfordshire and surrounding regions.
-
D.
SG
SG is the vehicle registration code used on license plates for the Swiss canton of St. Gallen.
-
E.
SG
SG is the vehicle registration code used on license plates for Spain’s Segovia Province.
- 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_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6b52cc1881909fb011d9a8af2e18 |
completed | April 1, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d02fd2a1e88190bc8d8c2b634399dd |
completed | April 3, 2026, 9:23 p.m. |
Created at: March 30, 2026, 7:10 p.m.