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I am testing Graphene, using the docker compose server API, sending the example text that should contain a TEMPORAL relation, but that is not being recognised.
POST Request (with Accept: application/json):
{"text": "Although the Treasury will announce details of the November refunding on Monday, the funding will be delayed if Congress and President Bush fail to increase the Treasury's borrowing capacity.", "doCoreference": "true", "isolateSentences": "false"}
Response:
{ "coreferenced": true, "sentences": [ { "originalSentence": "Although the Treasury 's will announce details of the November refunding on Monday , the funding will be delayed if Congress and President Bush fail to increase the Treasury 's borrowing capacity .", "sentenceIdx": 0, "extractionMap": { "0cc3f65ec23843568136bb06e3d9e5b6": { "id": "0cc3f65ec23843568136bb06e3d9e5b6", "type": "VERB_BASED", "confidence": null, "sentenceIdx": 0, "contextLayer": 0, "relation": "will announce", "arg1": "The Treasury 's", "arg2": "details of the November refunding", "linkedContexts": [ { "targetID": "013f570b9d06487f9aac5565f50bd746", "classification": "CONTRAST" }, { "targetID": "647225a2ae5c4518883c293781fdc715", "classification": "ELABORATION" } ], "simpleContexts": [ { "text": "on Monday .", "classification": "UNKNOWN_SUBORDINATION", "timeInformation": null } ] }, "013f570b9d06487f9aac5565f50bd746": { "id": "013f570b9d06487f9aac5565f50bd746", "type": "VERB_BASED", "confidence": null, "sentenceIdx": 0, "contextLayer": 0, "relation": "will be delayed", "arg1": "The funding", "arg2": "", "linkedContexts": [ { "targetID": "90fe9b01fc374113a04d813b7385a3fb", "classification": "CONDITION" }, { "targetID": "0cc3f65ec23843568136bb06e3d9e5b6", "classification": "CONTRAST" }, { "targetID": "647225a2ae5c4518883c293781fdc715", "classification": "ELABORATION" } ], "simpleContexts": [] }, "90fe9b01fc374113a04d813b7385a3fb": { "id": "90fe9b01fc374113a04d813b7385a3fb", "type": "VERB_BASED", "confidence": null, "sentenceIdx": 0, "contextLayer": 1, "relation": "fail", "arg1": "Bush", "arg2": "to increase the Treasury 's borrowing capacity", "linkedContexts": [], "simpleContexts": [] }, "647225a2ae5c4518883c293781fdc715": { "id": "647225a2ae5c4518883c293781fdc715", "type": "VERB_BASED", "confidence": null, "sentenceIdx": 0, "contextLayer": 1, "relation": "was", "arg1": "Bush", "arg2": "Congress and President", "linkedContexts": [], "simpleContexts": [] } } } ] }
Am i doing something wrong?
Thanks in advance
Chris
The text was updated successfully, but these errors were encountered:
Hi there.
I am testing Graphene, using the docker compose server API, sending the example text that should contain a TEMPORAL relation, but that is not being recognised.
POST Request (with Accept: application/json):
{"text": "Although the Treasury will announce details of the November refunding on Monday, the funding will be delayed if Congress and President Bush fail to increase the Treasury's borrowing capacity.", "doCoreference": "true", "isolateSentences": "false"}
Response:
{ "coreferenced": true, "sentences": [ { "originalSentence": "Although the Treasury 's will announce details of the November refunding on Monday , the funding will be delayed if Congress and President Bush fail to increase the Treasury 's borrowing capacity .", "sentenceIdx": 0, "extractionMap": { "0cc3f65ec23843568136bb06e3d9e5b6": { "id": "0cc3f65ec23843568136bb06e3d9e5b6", "type": "VERB_BASED", "confidence": null, "sentenceIdx": 0, "contextLayer": 0, "relation": "will announce", "arg1": "The Treasury 's", "arg2": "details of the November refunding", "linkedContexts": [ { "targetID": "013f570b9d06487f9aac5565f50bd746", "classification": "CONTRAST" }, { "targetID": "647225a2ae5c4518883c293781fdc715", "classification": "ELABORATION" } ], "simpleContexts": [ { "text": "on Monday .", "classification": "UNKNOWN_SUBORDINATION", "timeInformation": null } ] }, "013f570b9d06487f9aac5565f50bd746": { "id": "013f570b9d06487f9aac5565f50bd746", "type": "VERB_BASED", "confidence": null, "sentenceIdx": 0, "contextLayer": 0, "relation": "will be delayed", "arg1": "The funding", "arg2": "", "linkedContexts": [ { "targetID": "90fe9b01fc374113a04d813b7385a3fb", "classification": "CONDITION" }, { "targetID": "0cc3f65ec23843568136bb06e3d9e5b6", "classification": "CONTRAST" }, { "targetID": "647225a2ae5c4518883c293781fdc715", "classification": "ELABORATION" } ], "simpleContexts": [] }, "90fe9b01fc374113a04d813b7385a3fb": { "id": "90fe9b01fc374113a04d813b7385a3fb", "type": "VERB_BASED", "confidence": null, "sentenceIdx": 0, "contextLayer": 1, "relation": "fail", "arg1": "Bush", "arg2": "to increase the Treasury 's borrowing capacity", "linkedContexts": [], "simpleContexts": [] }, "647225a2ae5c4518883c293781fdc715": { "id": "647225a2ae5c4518883c293781fdc715", "type": "VERB_BASED", "confidence": null, "sentenceIdx": 0, "contextLayer": 1, "relation": "was", "arg1": "Bush", "arg2": "Congress and President", "linkedContexts": [], "simpleContexts": [] } } } ] }
Am i doing something wrong?
Thanks in advance
Chris
The text was updated successfully, but these errors were encountered: