Triple
T3248706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dollywood Foundation |
E68124
|
entity |
| Predicate | regionServed |
P82
|
FINISHED |
| Object | Australia |
E876
|
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: Australia | Statement: [Dollywood Foundation, regionServed, Australia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Australia Context triple: [Dollywood Foundation, regionServed, Australia]
-
A.
Australia
chosen
Australia is a large island continent and sovereign country in the Southern Hemisphere, known for its unique wildlife, diverse landscapes, and major cities such as Sydney and Melbourne.
-
B.
Tasmania
Tasmania is an island state of Australia known for its rugged wilderness, unique wildlife, and relatively cool maritime climate.
-
C.
AU
AU is the commonly used abbreviation for the African Union, a continental organization that promotes political and economic cooperation among African states.
-
D.
AU
AU is the commonly used abbreviation for Anna University, a prominent public technical university based in Chennai, India.
-
E.
AU
Aarhus University (AU) is a major public research university in Aarhus, Denmark, known for its broad range of academic programs and strong international profile.
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2771204e0819086ae2838a368589a |
completed | March 12, 2026, 8:19 a.m. |
Created at: March 8, 2026, 3:09 p.m.