Triple
T3847164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kunming Lake |
E85198
|
entity |
| Predicate | surfaceAreaShareOfSummerPalace |
P32345
|
FINISHED |
| Object | around 75 percent |
—
|
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: around 75 percent | Statement: [Kunming Lake, surfaceAreaShareOfSummerPalace, around 75 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surfaceAreaShareOfSummerPalace Context triple: [Kunming Lake, surfaceAreaShareOfSummerPalace, around 75 percent]
-
A.
surfaceAreaRelative
chosen
Indicates the ratio or comparative measure of one entity’s surface area relative to another reference surface area.
-
B.
hasBotanicalGardenArea_ha
Indicates that an entity possesses a botanical garden whose area is measured in hectares.
-
C.
numberOfPavilions
Indicates the total count of pavilions associated with a given entity or context.
-
D.
otherOfficialPalace
Indicates that one entity serves as another entity’s alternative or additional official palace.
-
E.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcb069881909d3536b18b7802a7 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.