Triple
T12935289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Bayamesa |
E309491
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Bayamo |
E130090
|
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: Bayamo | Statement: [La Bayamesa, associatedWith, Bayamo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bayamo Context triple: [La Bayamesa, associatedWith, Bayamo]
-
A.
Bayamo
chosen
Bayamo is one of Cuba’s oldest colonial cities, historically significant as an early Spanish settlement and a center of Cuban independence sentiment.
-
B.
Jarabacoa
Jarabacoa is a mountainous town in the Dominican Republic known for its cool climate, rivers, and outdoor adventure tourism.
-
C.
Aguas Buenas
Aguas Buenas is a mountainous municipality in central Puerto Rico known for its cool climate, caves, and scenic rural landscapes.
-
D.
San Juan de la Maguana
San Juan de la Maguana is a historic city in the western Dominican Republic known as a regional agricultural center and gateway to the country’s central mountain range.
-
E.
Guanabacoa
Guanabacoa is a historic municipality of Havana, Cuba, known for its colonial heritage and strong Afro-Cuban religious and cultural traditions.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97dc76d688190bd58a23351373666 |
completed | April 10, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbbf0fb08190aeb1697714942c2b |
completed | May 3, 2026, 4:14 a.m. |
Created at: April 9, 2026, 5:42 p.m.