Triple
T5523059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corydon, Kentucky |
E144857
|
entity |
| Predicate | hasStateAbbreviation |
P2461
|
FINISHED |
| Object | KY |
E251520
|
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: KY | Statement: [Corydon, Kentucky, hasStateAbbreviation, KY]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KY Context triple: [Corydon, Kentucky, hasStateAbbreviation, KY]
-
A.
KY
KY is the postcode area covering Kirkcaldy and surrounding parts of eastern Scotland.
-
B.
KY
chosen
KY is the official United States Postal Service abbreviation for the state of Kentucky.
-
C.
KE
KE is the two-letter ISO 3166-1 alpha-2 country code assigned to Kenya for international identification and data standards.
-
D.
KE
KE is the IATA airline designator for Korean Air, the flag carrier and largest airline of South Korea.
-
E.
KA
KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
- 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_69c008f873a481909b4d9f7e2db3c37d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f73cc8c8190a92a839c1ca804c7 |
completed | March 22, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c027f2e98c8190880752c9ae8aba4f |
completed | March 22, 2026, 5:33 p.m. |
Created at: March 22, 2026, 3:34 p.m.