Triple
T1959614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMMX |
E42350
|
entity |
| Predicate | focusCityFor |
P164
|
FINISHED |
| Object | Aeromar |
E42352
|
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: Aeromar | Statement: [MMMX, focusCityFor, Aeromar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aeromar Context triple: [MMMX, focusCityFor, Aeromar]
-
A.
Aeromar
chosen
Aeromar is a Mexican regional airline that primarily operates domestic and short-haul international flights, with a major operational base in Mexico City.
-
B.
MV Arlanza
MV Arlanza was a British ocean liner built by the renowned shipbuilding company Harland and Wolff for passenger and cargo service in the mid-20th century.
-
C.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
D.
Dorado
Dorado is a coastal municipality in northern Puerto Rico known for its upscale resorts, golf courses, and residential communities.
-
E.
Dorado
Dorado is a southern sky constellation known for containing most of the Large Magellanic Cloud and the southern portion of the Milky Way’s satellite galaxy.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb37f737881908130bb828affcaa2 |
completed | March 7, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbcea048819091d705095f0d3f68 |
completed | March 8, 2026, 10:44 p.m. |
Created at: March 4, 2026, 7:36 p.m.