EntityResolution batch. Close #6570 (#6602)

### What problem does this PR solve?

EntityResolution batch

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
This commit is contained in:
Zhichang Yu 2025-03-27 16:40:36 +08:00 committed by GitHub
parent d2043ff9f2
commit 36b62e0fab
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 28 additions and 20 deletions

View File

@ -63,7 +63,10 @@ class EntityResolution(Extractor):
self._resolution_result_delimiter_key = "resolution_result_delimiter"
self._input_text_key = "input_text"
async def __call__(self, graph: nx.Graph, prompt_variables: dict[str, Any] | None = None, callback: Callable | None = None) -> EntityResolutionResult:
async def __call__(self, graph: nx.Graph,
subgraph_nodes: set[str],
prompt_variables: dict[str, Any] | None = None,
callback: Callable | None = None) -> EntityResolutionResult:
"""Call method definition."""
if prompt_variables is None:
prompt_variables = {}
@ -88,16 +91,19 @@ class EntityResolution(Extractor):
candidate_resolution = {entity_type: [] for entity_type in entity_types}
for k, v in node_clusters.items():
candidate_resolution[k] = [(a, b) for a, b in itertools.combinations(v, 2) if self.is_similarity(a, b)]
candidate_resolution[k] = [(a, b) for a, b in itertools.combinations(v, 2) if (a in subgraph_nodes or b in subgraph_nodes) and self.is_similarity(a, b)]
num_candidates = sum([len(candidates) for _, candidates in candidate_resolution.items()])
callback(msg=f"Identified {num_candidates} candidate pairs")
resolution_result = set()
resolution_batch_size = 100
async with trio.open_nursery() as nursery:
for candidate_resolution_i in candidate_resolution.items():
if not candidate_resolution_i[1]:
continue
nursery.start_soon(lambda: self._resolve_candidate(candidate_resolution_i, resolution_result))
for i in range(0, len(candidate_resolution_i[1]), resolution_batch_size):
candidate_batch = candidate_resolution_i[0], candidate_resolution_i[1][i:i + resolution_batch_size]
nursery.start_soon(lambda: self._resolve_candidate(candidate_batch, resolution_result))
callback(msg=f"Resolved {num_candidates} candidate pairs, {len(resolution_result)} of them are selected to merge.")
change = GraphChange()
@ -118,7 +124,7 @@ class EntityResolution(Extractor):
change=change,
)
async def _resolve_candidate(self, candidate_resolution_i, resolution_result):
async def _resolve_candidate(self, candidate_resolution_i: tuple[str, list[tuple[str, str]]], resolution_result: set[str]):
gen_conf = {"temperature": 0.5}
pair_txt = [
f'When determining whether two {candidate_resolution_i[0]}s are the same, you should only focus on critical properties and overlook noisy factors.\n']

View File

@ -69,26 +69,27 @@ async def run_graphrag(
embedding_model,
callback,
)
new_graph = None
if subgraph:
new_graph = await merge_subgraph(
tenant_id,
kb_id,
doc_id,
subgraph,
embedding_model,
callback,
)
if not subgraph:
return
subgraph_nodes = set(subgraph.nodes())
new_graph = await merge_subgraph(
tenant_id,
kb_id,
doc_id,
subgraph,
embedding_model,
callback,
)
assert new_graph is not None
if not with_resolution or not with_community:
return
if new_graph is None:
new_graph = await get_graph(tenant_id, kb_id)
if with_resolution and new_graph is not None:
if with_resolution:
await resolve_entities(
new_graph,
subgraph_nodes,
tenant_id,
kb_id,
doc_id,
@ -96,7 +97,7 @@ async def run_graphrag(
embedding_model,
callback,
)
if with_community and new_graph is not None:
if with_community:
await extract_community(
new_graph,
tenant_id,
@ -223,6 +224,7 @@ async def merge_subgraph(
async def resolve_entities(
graph,
subgraph_nodes: set[str],
tenant_id: str,
kb_id: str,
doc_id: str,
@ -241,7 +243,7 @@ async def resolve_entities(
er = EntityResolution(
llm_bdl,
)
reso = await er(graph, callback=callback)
reso = await er(graph, subgraph_nodes, callback=callback)
graph = reso.graph
change = reso.change
callback(msg=f"Graph resolution removed {len(change.removed_nodes)} nodes and {len(change.removed_edges)} edges.")