Triple
T16919011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 佛香阁 |
E410393
|
entity |
| Predicate | 与昆明湖关系 |
P124717
|
FINISHED |
| Object | 居高临下俯视昆明湖全景 |
—
|
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: 居高临下俯视昆明湖全景 | Statement: [佛香阁, 与昆明湖关系, 居高临下俯视昆明湖全景]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 与昆明湖关系 Context triple: [佛香阁, 与昆明湖关系, 居高临下俯视昆明湖全景]
-
A.
isOneOfLargestInlandFreshwaterLakesInChina
Indicates that an entity belongs to the group of the largest inland freshwater lakes located within China.
-
B.
isPartOfChainOfLakes
Indicates that a lake belongs to and is one element within a connected sequence of lakes forming a chain.
-
C.
hasLakeThatRepresents
Indicates a relationship where a lake serves as a symbolic or representative feature for something, such as a place, concept, or entity.
-
D.
connectsToByLake
Indicates that one entity is linked or joined to another specifically via a lake as the connecting medium or route.
-
E.
refersToNaturalWonder
Indicates that one entity makes reference to, mentions, or points specifically to a natural wonder (such as a notable natural landmark or formation).
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cdec3d0c8190994a0fca335c65d6 |
completed | April 18, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32d7aae948190bc238d765795688c |
completed | April 18, 2026, 7:06 a.m. |
Created at: April 10, 2026, 5:30 a.m.