Triple
T20618230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cremorne Tower |
E506621
|
entity |
| Predicate | isElementOfUrbanLandscape |
P124480
|
FINISHED |
| Object | Chelsea riverside 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: Chelsea riverside skyline | Statement: [Cremorne Tower, isElementOfUrbanLandscape, Chelsea riverside skyline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isElementOfUrbanLandscape Context triple: [Cremorne Tower, isElementOfUrbanLandscape, Chelsea riverside skyline]
-
A.
isInUrbanContext
Indicates that something exists, occurs, or is situated within an urban or city-based environment or setting.
-
B.
isUrbanNode
Indicates that a location or entity functions as an urban center or node within a city or metropolitan network.
-
C.
isPartOfStreetscape
Indicates that something forms a component or element within the overall layout or visual composition of a streetscape.
-
D.
isUrbanPark
Indicates that a location is designated and used as a public park within an urban or metropolitan area.
-
E.
isUrbanLandmark
chosen
Indicates that a place or structure is recognized as a notable or significant landmark within an urban environment.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abdf9d7c8190969247a4ae55b781 |
completed | April 20, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.