Triple
T14533401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rivertown Junction |
E340971
|
entity |
| Predicate | locatedInParkSectionGroup |
P114811
|
FINISHED |
| Object | front areas of Dollywood |
—
|
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: front areas of Dollywood | Statement: [Rivertown Junction, locatedInParkSectionGroup, front areas of Dollywood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInParkSectionGroup Context triple: [Rivertown Junction, locatedInParkSectionGroup, front areas of Dollywood]
-
A.
positionInPark
Indicates that one entity occupies a specific location or spot within a park.
-
B.
locatedInParkVicinity
Indicates that an entity is situated in the area immediately surrounding or near a park.
-
C.
hasParkSection
Indicates that one entity includes, contains, or is associated with a specific section or area of a park.
-
D.
inPark
Indicates that one entity is located within or inside the boundaries of a park.
-
E.
parkSection
Indicates a relationship where a specific area or subsection belongs to, is contained within, or is designated as part of a larger park.
- F. None of above. chosen
Provenance (4 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea053f9bc8190901b9d321811d881 |
completed | April 14, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c546c7081909e27d504ec360c5c |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de610330a48190b558235a14c0dc9f |
completed | April 14, 2026, 3:45 p.m. |
Created at: April 10, 2026, 1:22 a.m.