Triple
T13427561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cora language |
E313521
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Santa Teresa Cora |
E313524
|
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: Santa Teresa Cora | Statement: [Cora language, hasDialect, Santa Teresa Cora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Teresa Cora Context triple: [Cora language, hasDialect, Santa Teresa Cora]
-
A.
Santa Teresa Cora
chosen
Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
-
B.
Santa Rosalía
Santa Rosalía is a historic mining town and port on the eastern coast of the Baja California Peninsula in Mexico, known for its French-influenced architecture and copper mining heritage.
-
C.
Teresa
Teresa is the middle name of Tamar Teresa Day Hennessy.
-
D.
Teresa
Teresa is a feminine given name commonly used in various cultures, often associated with notable religious and historical figures.
-
E.
Teresa
Teresa is the central protagonist of the play "The Memory of Water," around whom the story’s emotional and familial conflicts revolve.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed1f9208190bf5ef5b8a7ded376 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f730883cb48190add9469c48dc3e89 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:40 p.m.