Triple
T9503379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiayu County |
E229198
|
entity |
| Predicate | hasRiverineFeature |
P165
|
FINISHED |
| Object | Yangtze River shoreline |
—
|
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: Yangtze River shoreline | Statement: [Jiayu County, hasRiverineFeature, Yangtze River shoreline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverineFeature Context triple: [Jiayu County, hasRiverineFeature, Yangtze River shoreline]
-
A.
hasRiver
chosen
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
B.
riverFeatureType
Indicates the specific kind or category of physical or functional feature associated with a river (e.g., source, mouth, tributary, channel segment).
-
C.
isWatercourseOf
Indicates that a watercourse (such as a river or stream) flows through, belongs to, or is geographically associated with a particular area or feature.
-
D.
hasWaterFeatures
Indicates that an entity includes or is associated with water-related elements such as fountains, ponds, streams, or similar features.
-
E.
hasWatercourseType
Indicates the specific kind or category of watercourse (such as river, stream, or canal) associated with an entity.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9840148081908df237f212b62e67 |
completed | April 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cca567ca448190bf4bcce8ce7dd54f |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:57 p.m.