Triple
T2957356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cora |
E79964
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Santa Teresa Cora
Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
|
E313524
|
NE FINISHED |
How this triple was built (4 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, hasDialect, Santa Teresa Cora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Teresa Cora Context triple: [Cora, hasDialect, Santa Teresa Cora]
-
A.
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.
-
B.
Teresa
Teresa is the religious name of Mother Teresa, the Catholic nun and missionary renowned for her charitable work with the poor in Kolkata, India.
-
C.
Santa Teresa
Santa Teresa is a historic, bohemian hilltop neighborhood in Rio de Janeiro known for its winding streets, colonial mansions, and vibrant arts scene.
-
D.
Clementina
Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
-
E.
Fernanda
Fernanda is a feminine given name commonly used in Romance-language countries, derived from the masculine name Ferdinand.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Santa Teresa Cora Triple: [Cora, hasDialect, Santa Teresa Cora]
Generated description
Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santa Teresa Cora Target entity description: Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
-
A.
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.
-
B.
Teresa
Teresa is the religious name of Mother Teresa, the Catholic nun and missionary renowned for her charitable work with the poor in Kolkata, India.
-
C.
Santa Teresa
Santa Teresa is a historic, bohemian hilltop neighborhood in Rio de Janeiro known for its winding streets, colonial mansions, and vibrant arts scene.
-
D.
Clementina
Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
-
E.
Fernanda
Fernanda is a feminine given name commonly used in Romance-language countries, derived from the masculine name Ferdinand.
- F. None of above. chosen
Provenance (5 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad992b33e081909d22a19d5064c47d |
completed | March 8, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc8a10848190b8eec482252eb76b |
completed | March 11, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69b0fd407bd08190b62788e8d1cdd205 |
completed | March 11, 2026, 5:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0fd91541c8190a481b55eb9b0ac35 |
completed | March 11, 2026, 5:28 a.m. |
Created at: March 8, 2026, 2:57 p.m.