Triple
T18241231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las Mercedes Airport |
E436815
|
entity |
| Predicate | servesAsHubFor |
P423
|
FINISHED |
| Object | La Costeña |
—
|
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: La Costeña | Statement: [Las Mercedes Airport, servesAsHubFor, La Costeña]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Costeña Context triple: [Las Mercedes Airport, servesAsHubFor, La Costeña]
-
A.
La Costeña
chosen
La Costeña is a Nicaraguan regional airline that operates domestic flights connecting Managua with various destinations across the country.
-
B.
Costa Chica
Costa Chica is a coastal region in southern Mexico known for its Afro-Mexican communities, rich cultural traditions, and Pacific shoreline spanning parts of Oaxaca and Guerrero.
-
C.
San Blas
San Blas is the Spanish name for Saint Blaise, a Christian bishop and martyr venerated as a patron saint of throat ailments.
-
D.
San Blas
San Blas is a Madrid Metro station serving the San Blas-Canillejas district in the east of Madrid, Spain.
-
E.
San Blas
San Blas is a small settlement in Cuba’s Ciénaga de Zapata region, known for its proximity to extensive wetlands and rich biodiversity.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e287548190b666a990e5b168b0 |
completed | April 19, 2026, 3:42 p.m. |
Created at: April 10, 2026, 10:33 a.m.