Triple
T19579332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cibao region |
E489945
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | La Vega |
—
|
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 Vega | Statement: [Cibao region, containsCity, La Vega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Vega Context triple: [Cibao region, containsCity, La Vega]
-
A.
La Vega
chosen
La Vega is a major city in the fertile Cibao region of the Dominican Republic, known for its agriculture and vibrant Carnival celebrations.
-
B.
La Vega
La Vega is a town and municipality in Colombia known for its lush mountainous landscapes and proximity to Bogotá.
-
C.
San Juan del Cesar
San Juan del Cesar is a municipality and town in northeastern Colombia known for its agricultural activities and cultural traditions within the La Guajira Department.
-
D.
Bocanegra
Bocanegra is a Spanish-origin surname borne by various notable figures, including Mexican politician and brief interim president José María Bocanegra.
-
E.
Santo Domingo de los Colorados
Santo Domingo de los Colorados is a major city in western Ecuador known as a commercial and transportation hub between the coast and the Andean highlands.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6402763b8819099e535979f094f9d |
completed | April 20, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:42 p.m.