Triple
T38169689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hezhenyu |
E1000036
|
entity |
| Predicate | usedAlongRivers |
P168268
|
FINISHED |
| Object | Amur River |
—
|
NE NERFINISHED |
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: Amur River | Statement: [Hezhenyu, usedAlongRivers, Amur River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAlongRivers Context triple: [Hezhenyu, usedAlongRivers, Amur River]
-
A.
isSpokenAlongRiver
chosen
Indicates that a language or dialect is used or spoken by communities located along a particular river or river system.
-
B.
usesWaterwaysFor
Indicates that one entity relies on or employs waterways as a means or route to perform an activity or function in relation to another entity.
-
C.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
D.
useRiverSystems
Indicates that an entity utilizes or manages river systems for a particular purpose or function.
-
E.
linkedToRiver
Indicates a relationship where something is physically or functionally connected to, associated with, or dependent on a river.
- 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_69f76daaace48190a38cee37f8ce343f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff1c91bbac8190b84012dee1cb3b2c |
completed | May 9, 2026, 11:37 a.m. |
| PD | Predicate disambiguation | batch_69ff1c23ca508190bb5a435d765b7e53 |
completed | May 9, 2026, 11:36 a.m. |
Created at: May 3, 2026, 4:29 p.m.