Triple

T28988970
Position Surface form Disambiguated ID Type / Status
Subject 大冶市 E734769 entity
Predicate legislativeBody P239 FINISHED
Object 大冶市人民代表大会
大冶市人民代表大会是湖北省大冶市的地方国家权力机关，负责行使立法、监督及重大事项决定等职权。
 E1843770 NE 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: 大冶市人民代表大会 | Statement: [大冶市, legislativeBody, 大冶市人民代表大会]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 大冶市人民代表大会
Triple: [大冶市, legislativeBody, 大冶市人民代表大会]
Generated description
大冶市人民代表大会是湖北省大冶市的地方国家权力机关，负责行使立法、监督及重大事项决定等职权。

Provenance (5 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_69f05b0dd9b481908b7901e1c95ff6b2 completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65f7bc2748190bced1b468962b99d completed May 2, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2505b62ffc819081c143e18231ef7f completed June 7, 2026, 5:46 a.m.
NEDg Description generation batch_6a2509d511b481908fb354a22e7ee542 completed June 7, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a250e374f348190a35e6037d4820e47 completed June 7, 2026, 6:22 a.m.
Created at: April 28, 2026, 9:16 a.m.