Triple
T5378090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carolina |
E113010
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Canóvanas |
E51856
|
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: Canóvanas | Statement: [Carolina, borders, Canóvanas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canóvanas Context triple: [Carolina, borders, Canóvanas]
-
A.
Canóvanas
chosen
Canóvanas is a municipality in northeastern Puerto Rico known for its proximity to San Juan and its blend of suburban communities with rural, mountainous landscapes.
-
B.
Cajeme
Cajeme is a major municipality and agricultural and industrial center in the southern part of the Mexican state of Sonora, best known for its main city Ciudad Obregón.
-
C.
Cauqui
Cauqui is an indigenous Aymaran language variety spoken by a small community in the Andean region of Peru.
-
D.
Vinantes
Vinantes is a small French commune located in the Seine-et-Marne department in the Île-de-France region in north-central France.
-
E.
Chaguanas
Chaguanas is a rapidly growing commercial and residential hub on the island of Trinidad, known for its bustling markets and diverse population.
- 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_69bd4436a1988190af18dcff7fd306b4 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd86cb13ac81909dc364e7d3605844 |
completed | March 20, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf29465ff0819082c05dbe40a306f3 |
completed | March 21, 2026, 11:27 p.m. |
Created at: March 20, 2026, 2:03 p.m.