Triple

T36128560
Position Surface form Disambiguated ID Type / Status
Subject “八一”军旗 E1044951 entity
Predicate 使用主体 P184725 FINISHED
Object 中国人民解放军联勤保障部队
中国人民解放军联勤保障部队是负责为全军提供统一高效后勤与联勤保障支持的中国人民解放军直属保障力量。
 E2170865 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: 中国人民解放军联勤保障部队 | Statement: [“八一”军旗, 使用主体, 中国人民解放军联勤保障部队]
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: 中国人民解放军联勤保障部队
Triple: [“八一”军旗, 使用主体, 中国人民解放军联勤保障部队]
Generated description
中国人民解放军联勤保障部队是负责为全军提供统一高效后勤与联勤保障支持的中国人民解放军直属保障力量。

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_69f76e356c908190abc6ca1e6a05b011 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b4c58cac819085562a228aac3d9b completed May 3, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38de1321348190a10da47fcb564fe7 completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38fafba2ec8190bf3bbd567a8d13bf completed June 22, 2026, 9:06 a.m.
NED2 Entity disambiguation (via description) batch_6a38fbe826e08190a861f5fc88d8da9d completed June 22, 2026, 9:10 a.m.
Created at: May 3, 2026, 4:08 p.m.