Triple
T19408967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colorado Mesa University |
E485538
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | CMU |
—
|
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: CMU | Statement: [Colorado Mesa University, shortName, CMU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CMU Context triple: [Colorado Mesa University, shortName, CMU]
-
A.
CMU
CMU is a private research university in Pittsburgh, Pennsylvania, renowned for its leading programs in computer science, engineering, and the arts.
-
B.
CMU
chosen
CMU is a public university in Grand Junction, Colorado, known for its diverse undergraduate programs and strong regional presence on the Western Slope.
-
C.
CMU
CMU is a major medical university located in Shenyang, China, known for its education and research in clinical medicine and related health sciences.
-
D.
CMU
CMU is a major public research university in Chiang Mai, Thailand, known for its comprehensive academic programs and role as a leading educational institution in northern Thailand.
-
E.
CMU College of Engineering
CMU College of Engineering is the engineering school of Carnegie Mellon University, renowned for its cutting-edge research and education in areas such as robotics, computer engineering, and materials science.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af3eaa081909e9537a2c57dc6c1 |
completed | April 20, 2026, 1:32 p.m. |
Created at: April 10, 2026, 1:37 p.m.