Triple
T2262833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TAR Aerolíneas |
E50075
|
entity |
| Predicate | focusCity |
P164
|
FINISHED |
| Object | Mazatlán |
E107504
|
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: Mazatlán | Statement: [TAR Aerolíneas, focusCity, Mazatlán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mazatlán Context triple: [TAR Aerolíneas, focusCity, Mazatlán]
-
A.
Manzanillo
Manzanillo is a major Pacific coastal city in western Mexico known for its busy commercial port and popular beach tourism.
-
B.
Mazatlán, Mexico
chosen
Mazatlán, Mexico is a Pacific coastal city in the state of Sinaloa known for its long sandy beaches, historic old town, and major seaport and tourism industry.
-
C.
Puerto Vallarta
Puerto Vallarta is a popular Pacific coast resort city in the Mexican state of Jalisco, known for its beaches, nightlife, and vibrant arts and cultural scene.
-
D.
Culiacán
Culiacán is the largest city and main economic and cultural center of the Mexican state of Sinaloa.
-
E.
Punta de Mita
Punta de Mita is a luxury beach resort area on Mexico’s Pacific coast known for its upscale hotels, surfing, and proximity to the Bay of Banderas and the Marietas Islands.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc18be8308190abc4a59d37dfd93a |
completed | March 7, 2026, 6:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae894a20e0819097f08959f7a062ef |
completed | March 9, 2026, 8:48 a.m. |
Created at: March 4, 2026, 7:48 p.m.