Triple
T8868897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bosten Lake |
E211094
|
entity |
| Predicate | isOneOfLargestInlandFreshwaterLakesInChina |
P85448
|
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: [Bosten Lake, isOneOfLargestInlandFreshwaterLakesInChina, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfLargestInlandFreshwaterLakesInChina Context triple: [Bosten Lake, isOneOfLargestInlandFreshwaterLakesInChina, true]
-
A.
isOneOfLargestArtificialLakesIn
Indicates that a lake ranks among the largest artificial (man-made) lakes within a specified region or area.
-
B.
isOneOfLargestLakesByArea
Indicates that the subject lake ranks among the largest lakes in terms of surface area.
-
C.
isAmongLargestHighAltitudeLakes
Indicates that a lake ranks among the largest lakes located at high altitudes.
-
D.
isLargestFreshwaterLakeIn
Indicates that a lake is the largest freshwater lake within the specified geographic region or area.
-
E.
isSecondLargestLakeIn
Indicates that a lake is the second largest lake within a specified geographic region or 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_69ca838d3c7c8190a849566d5afd2b11 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61241d048190aead14a8f5589856 |
completed | April 1, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2956788190a311c647b4da17a6 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5d6e54808190af4156edd4c8ffbc |
completed | March 31, 2026, 11:49 p.m. |
Created at: March 30, 2026, 6:51 p.m.