Triple

T38354397

Position	Surface form	Disambiguated ID	Type / Status
Subject	PLA Marine Corps	`E1046286`	entity
Predicate	nativeName	`P15`	FINISHED
Object	中国人民解放军海军陆战队中国人民解放军海军陆战队是中国人民解放军海军所属的两栖作战部队，主要承担登陆作战、岛礁防御和海外任务等多样化军事行动。	`E2265918`	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: 中国人民解放军海军陆战队 | Statement: [PLA Marine Corps, nativeName, 中国人民解放军海军陆战队]

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: 中国人民解放军海军陆战队
Triple: [PLA Marine Corps, nativeName, 中国人民解放军海军陆战队]

Generated description

中国人民解放军海军陆战队是中国人民解放军海军所属的两栖作战部队，主要承担登陆作战、岛礁防御和海外任务等多样化军事行动。

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_69f76e3a94fc81908edc175e8d259e80`	completed	May 3, 2026, 3:48 p.m.
NER	Named-entity recognition	`batch_69fcc7338120819081cb46547d60f2cb`	completed	May 7, 2026, 5:09 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a41a7fd71788190a4928633e49afa62`	completed	June 28, 2026, 11:02 p.m.
NEDg	Description generation	`batch_6a41a90ed25c81908dcdbb7e687394c5`	completed	June 28, 2026, 11:06 p.m.
NED2	Entity disambiguation (via description)	`batch_6a41a9aecf108190a0833bde27cb0e6a`	completed	June 28, 2026, 11:09 p.m.

Created at: May 3, 2026, 4:31 p.m.