Triple
T27700030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wormleysburg, Pennsylvania |
E698401
|
entity |
| Predicate | hasRiverViewOf |
P90917
|
FINISHED |
| Object | Harrisburg skyline |
—
|
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: Harrisburg skyline | Statement: [Wormleysburg, Pennsylvania, hasRiverViewOf, Harrisburg skyline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverViewOf Context triple: [Wormleysburg, Pennsylvania, hasRiverViewOf, Harrisburg skyline]
-
A.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
B.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
C.
hasWaterfrontView
chosen
Indicates that a property or location offers a direct view of a body of water from its premises.
-
D.
riverPanorama
Indicates a wide, scenic view or visual representation that prominently features a river and its surrounding landscape.
-
E.
hasRiverBeach
Indicates that a location includes or is characterized by a beach area along a river.
- 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 27, 2026, 2:56 p.m.