Triple
T3605415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Granite Railway |
E76357
|
entity |
| Predicate | hasInclineSection |
P25297
|
FINISHED |
| Object | plane to lower granite to the wharf |
—
|
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: plane to lower granite to the wharf | Statement: [Granite Railway, hasInclineSection, plane to lower granite to the wharf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInclineSection Context triple: [Granite Railway, hasInclineSection, plane to lower granite to the wharf]
-
A.
hasIncline
chosen
Indicates that one entity possesses or exhibits a slope, tilt, or upward/downward angle relative to another reference.
-
B.
hasSettlementOnSlopes
Indicates that a settlement is located on or extends across the slopes of a landform such as a hill or mountain.
-
C.
hasScenicSections
Indicates that a route, path, or area contains segments that are visually attractive or offer notable scenic views.
-
D.
hasCliff
Indicates that something possesses or features a steep, high rock face or abrupt vertical drop as part of its structure or environment.
-
E.
hasSpiralRampLength
Indicates the length measurement of a spiral-shaped ramp in the relationship.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc1e1f9188190b481c26b7f561db7 |
completed | March 8, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69adb83d8b1c8190b3bddbc5dc995a87 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.