Triple
T9453854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piedmont Province in Pennsylvania |
E227963
|
entity |
| Predicate | containsLandforms |
P940
|
FINISHED |
| Object | broad ridges |
—
|
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: broad ridges | Statement: [Piedmont Province in Pennsylvania, containsLandforms, broad ridges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsLandforms Context triple: [Piedmont Province in Pennsylvania, containsLandforms, broad ridges]
-
A.
hasLandform
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
B.
connectsLandform
Indicates a relationship where one landform serves as a physical link or passage between two or more other landforms.
-
C.
hasLandformOrigin
Indicates that something originates from, or is formed by, a particular landform.
-
D.
landerType
Indicates the specific kind or category of lander involved in the relationship or action.
-
E.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
- 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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f8c7b3481909c1182b41d8c27a9 |
completed | April 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:52 p.m.