Triple
T16823986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vermont |
E408966
|
entity |
| Predicate | postalAbbreviation |
P43
|
FINISHED |
| Object | VT |
E61297
|
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: VT | Statement: [Vermont, postalAbbreviation, VT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VT Context triple: [Vermont, postalAbbreviation, VT]
-
A.
VT
chosen
VT is the standard two-letter postal abbreviation used to represent the U.S. state of Vermont.
-
B.
VT
VT is the commonly used abbreviation for Virginia Tech, a major public research university in Blacksburg, Virginia.
-
C.
VT
VT is the vehicle registration code used on license plates for vehicles registered in the Province of Viterbo in Italy.
-
D.
VG
VG is the two-letter ISO 3166 country code assigned to the British Virgin Islands.
-
E.
VG
VG is a major Norwegian newspaper and online news outlet known for its wide national readership and influential coverage of current affairs.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b310ffec81908087e5aaacc4a7c2 |
completed | April 18, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b29c170c81908fcc88c31e266ffb |
completed | May 10, 2026, 4:30 p.m. |
Created at: April 10, 2026, 5:23 a.m.