Triple
T10190351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MU |
E238015
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object | MU |
unclear NED1
|
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: MU | Statement: [MU, acronym, MU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MU Context triple: [MU, acronym, MU]
-
A.
MU
MU is the IATA airline designator assigned to China Eastern Airlines, one of China’s major carriers.
-
B.
MU
MU is the commonly used abbreviation for the University of Missouri, a major public research university based in Columbia, Missouri.
-
C.
MU
MU is the common abbreviation for Masaryk University, a major public research university located in Brno, Czech Republic.
-
D.
UM
UM is the commonly used abbreviation for the University of Miami, a private research university located in Coral Gables, Florida.
-
E.
UM
UM is the regional vehicle registration code used for the district of Uckermark in the German state of Brandenburg.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7d6fdc81908052866495b6574f |
completed | April 2, 2026, 4:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d317c0c22881909ed388721e80bafd |
completed | April 6, 2026, 2:17 a.m. |
Created at: March 30, 2026, 9:13 p.m.