Triple
T12500822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catholic University of Santa Fe |
E298813
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Santa Fe |
E592450
|
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 Fe | Statement: [Catholic University of Santa Fe, city, Santa Fe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Fe Context triple: [Catholic University of Santa Fe, city, Santa Fe]
-
A.
Santa Fe
Santa Fe is a town on Cuba’s Isla de la Juventud, known as one of the island’s principal local settlements.
-
B.
Santa Fe
chosen
Santa Fe is the capital city of New Mexico, known for its Pueblo-style architecture, vibrant arts scene, and rich blend of Native American and Spanish colonial history.
-
C.
Santa Fe
Santa Fe is a major modern business and financial district in western Mexico City known for its corporate offices, upscale shopping centers, and contemporary high-rise architecture.
-
D.
Santa Fe
Santa Fe was a major American railroad company that played a key role in the development and transportation infrastructure of the western United States.
-
E.
Santa Fe
Santa Fe is a small coastal municipality in the island province of Romblon in the Philippines, known for its rural communities and surrounding marine scenery.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfbb2a48190a231b02cfa990565 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f6ed57c8190a365998cd53be873 |
completed | May 3, 2026, 5:01 p.m. |
Created at: April 8, 2026, 9:57 p.m.