Triple
T14545819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sydney–Melbourne air route |
E341288
|
entity |
| Predicate | IATAAirportCodeDestination |
P45615
|
FINISHED |
| Object | MEL |
E158312
|
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: MEL | Statement: [Sydney–Melbourne air route, IATAAirportCodeDestination, MEL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MEL Context triple: [Sydney–Melbourne air route, IATAAirportCodeDestination, MEL]
-
A.
MEL
chosen
MEL is the three-letter IATA airport code for Melbourne Airport, the primary international gateway serving Melbourne, Australia.
-
B.
Mello
Mello is the official mascot character created for the 2007 ICC Cricket World Cup held in the West Indies.
-
C.
MEG
MEG is the stock ticker symbol of Megaworld Corporation, a major Philippine real estate developer known for its large-scale township projects.
-
D.
mello
mello is a digital-first mortgage and lending platform developed by loanDepot to streamline and modernize the home loan experience.
-
E.
Mel
Mel is a common shortened form of the given name Melissa, often used as a casual or affectionate nickname.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1bfc2b48190adb0897682c26a9a |
completed | April 14, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a60f2f88190b08fdf0a3095d0a7 |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.