Triple
T26880556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cumberland, Maine |
E676879
|
entity |
| Predicate | CumberlandFairFocus |
P58216
|
FINISHED |
| Object | agriculture and livestock exhibitions |
—
|
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: agriculture and livestock exhibitions | Statement: [Cumberland, Maine, CumberlandFairFocus, agriculture and livestock exhibitions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CumberlandFairFocus Context triple: [Cumberland, Maine, CumberlandFairFocus, agriculture and livestock exhibitions]
-
A.
hasCountyFair
chosen
Indicates that a place or region hosts or holds a county fair event.
-
B.
worldsFairEdition
Indicates that one entity is a special edition of another that was produced or designated specifically for a World's Fair event.
-
C.
celebrationFocus
Indicates that the primary subject or emphasis of a celebration is directed toward a particular entity or theme.
-
D.
Apple-ScrappleFestivalFeatures
Indicates that the Apple-Scrapple Festival includes or showcases a particular feature, attraction, or element.
-
E.
festivalFocus
Indicates that a festival is centered around, dedicated to, or thematically focused on a particular subject, activity, or feature.
- 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_69eee9bb44988190b6e11652d028bc59 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61f1c9c888190a3b8711c2d35036b |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:39 a.m.