Triple
T2761323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VMI Keydets |
E61225
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | VMI |
E60381
|
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: VMI | Statement: [VMI Keydets, abbreviation, VMI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VMI Context triple: [VMI Keydets, abbreviation, VMI]
-
A.
VMI
chosen
VMI is a public military college in Lexington, Virginia, known for its rigorous academic and military training programs.
-
B.
VEMN
VEMN is the ICAO airport code assigned to Dibrugarh Airport in Assam, India.
-
C.
VU
VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
-
D.
VMS
VMS is a multiuser, multitasking operating system originally created by Digital Equipment Corporation for its VAX minicomputers, known for its robustness, security features, and influence on later systems like Windows NT.
-
E.
VMS
VMS is a regional public transport association in the Chemnitz area of Germany that coordinates and manages integrated fares and services across multiple transit operators.
- 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd2281b8819094c22ce5e4753bd3 |
completed | March 7, 2026, 8:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc04365448190b37e5ed16c16d650 |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 6, 2026, 9:57 p.m.