Triple
T15947777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vermont, Wisconsin |
E386728
|
entity |
| Predicate | stateCode |
P20781
|
FINISHED |
| Object | WI |
E16627
|
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: WI | Statement: [Vermont, Wisconsin, stateCode, WI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WI Context triple: [Vermont, Wisconsin, stateCode, WI]
-
A.
WI
WI is the vehicle registration code used on license plates for the German city of Wiesbaden.
-
B.
Wisconsin
chosen
Wisconsin is a U.S. state in the Upper Midwest known for its dairy industry, Great Lakes shorelines, and mix of rural landscapes and industrial cities.
-
C.
WA
WA is the commonly used abbreviation for World Archery, the international governing body for the sport of archery.
-
D.
WA
WA is the IATA airline designator assigned to KLM Cityhopper, the regional subsidiary of KLM Royal Dutch Airlines.
-
E.
WA
WA is a UK postcode area covering parts of Warrington and surrounding towns in northwest England.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156d2fda8819085279d2a0f8a02ab |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5c0c8a481908aa7a40bca15e38e |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:53 a.m.