Triple
T12509266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xixi National Wetland Park |
E299030
|
entity |
| Predicate | isUrbanWetland |
P105333
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Xixi National Wetland Park, isUrbanWetland, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanWetland Context triple: [Xixi National Wetland Park, isUrbanWetland, true]
-
A.
isUrbanLake
Indicates that a given lake is located within or closely associated with an urban or metropolitan area.
-
B.
isUrbanForest
Indicates that an area of trees and vegetation is located within or closely integrated with an urban or suburban environment.
-
C.
containsWetland
Indicates that one area or region includes within its boundaries a wetland ecosystem.
-
D.
isCoastalWetlandCity
Indicates that a city is located within or adjacent to a coastal wetland area, such as marshes, mangroves, or tidal flats.
-
E.
isUrbanWaterway
Indicates that a waterway is located within, passes through, or primarily serves an urban or metropolitan area.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954b715fc819091fa84430be46273 |
completed | April 10, 2026, 7:51 p.m. |
Created at: April 8, 2026, 9:57 p.m.