Triple

T28373985
Position Surface form Disambiguated ID Type / Status
Subject 十堰市人民政府 E718705 entity
Predicate hasDivision P35 FINISHED
Object 十堰市人力资源和社会保障局
十堰市人力资源和社会保障局是负责十堰市人力资源管理、就业促进、社会保险及劳动关系等工作的市级政府职能部门。
 E1815248 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: 十堰市人力资源和社会保障局 | Statement: [十堰市人民政府, hasDivision, 十堰市人力资源和社会保障局]
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: 十堰市人力资源和社会保障局
Triple: [十堰市人民政府, hasDivision, 十堰市人力资源和社会保障局]
Generated description
十堰市人力资源和社会保障局是负责十堰市人力资源管理、就业促进、社会保险及劳动关系等工作的市级政府职能部门。

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_69eff6ee5afc8190bd7375a29f0cc6c6 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64c5c0ba081908d836393db68b842 completed May 2, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627d7983c8190aa0aac8255cddaab completed May 26, 2026, 11:08 p.m.
NEDg Description generation batch_6a162923e55481909c09ac79ce541641 completed May 26, 2026, 11:13 p.m.
NED2 Entity disambiguation (via description) batch_6a1629baced481908056a997a85a1b84 completed May 26, 2026, 11:16 p.m.
Created at: April 28, 2026, 1:01 a.m.