Triple
T14314628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leatherstocking Country |
E354922
|
entity |
| Predicate | marketingRegionFor |
P50747
|
FINISHED |
| Object | regional tourism promotion in New York State |
—
|
LITERAL 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: regional tourism promotion in New York State | Statement: [Leatherstocking Country, marketingRegionFor, regional tourism promotion in New York State]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marketingRegionFor Context triple: [Leatherstocking Country, marketingRegionFor, regional tourism promotion in New York State]
-
A.
marketRegion
Indicates the geographic or demographic area in which a product, service, or entity is actively marketed or targeted.
-
B.
campaignRegion
chosen
Indicates the geographic area or territory in which a campaign is conducted or targeted.
-
C.
serviceRegion
Indicates the geographic area or jurisdiction within which a service is provided or applicable.
-
D.
exportRegion
Indicates the region or geographic area from which goods, services, or resources are exported.
-
E.
landingRegion
Indicates the area or zone where an object or entity comes to rest or makes contact after moving or descending.
- F. None of above.
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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b49e5481909b9ffab2d922e284 |
completed | April 14, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a9515f4819081aabf251bca5878 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:12 a.m.