Triple
T38128436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poyang County |
E952148
|
entity |
| Predicate | hasLargestNearbyLakeCharacteristic |
P201631
|
FINISHED |
| Object | largest freshwater lake in China |
—
|
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: largest freshwater lake in China | Statement: [Poyang County, hasLargestNearbyLakeCharacteristic, largest freshwater lake in China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLargestNearbyLakeCharacteristic Context triple: [Poyang County, hasLargestNearbyLakeCharacteristic, largest freshwater lake in China]
-
A.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
-
B.
hasNearbyLakeRegion
Indicates that one region is located close to a lake or lake-dominated area.
-
C.
hasMajorLake
Indicates that a geographic region or area contains at least one significant lake within its boundaries.
-
D.
nearbyLargerLake
Indicates that one entity is a lake located near another lake that is larger in size.
-
E.
hasLakeLandscape
Indicates that an entity features or is characterized by a landscape that includes a lake.
- 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_69f76f083548819082bd2bbf53c79e8e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a000efe971081909de03f875a7ad6cc |
completed | May 10, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_6a000c4ffe788190a5757af60aadd9f3 |
completed | May 10, 2026, 4:40 a.m. |
| PDg | Predicate description generation | batch_6a000efdbe948190b4bfa9871aa1a7ee |
completed | May 10, 2026, 4:52 a.m. |
Created at: May 3, 2026, 4:21 p.m.