Triple

T27774307

Position	Surface form	Disambiguated ID	Type / Status
Subject	Chronicles of Huayang	`E699142`	entity
Predicate	originalTitle	`P65`	FINISHED
Object	華陽國志華陽國志 is an early Chinese historical and geographical work from the Jin dynasty that records the history, culture, and local traditions of the Sichuan and surrounding southwestern regions.	`E1788790`	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: 華陽國志 | Statement: [Chronicles of Huayang, originalTitle, 華陽國志]

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: 華陽國志
Triple: [Chronicles of Huayang, originalTitle, 華陽國志]

Generated description

華陽國志 is an early Chinese historical and geographical work from the Jin dynasty that records the history, culture, and local traditions of the Sichuan and surrounding southwestern regions.

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_69ef6a4b5a9081909c9111396c2be3d2`	completed	April 27, 2026, 1:53 p.m.
NER	Named-entity recognition	`batch_69f63798a67c8190876c47dacf89af6e`	completed	May 2, 2026, 5:42 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a12ecbd5a308190bc56732476a508c6`	completed	May 24, 2026, 12:19 p.m.
NEDg	Description generation	`batch_6a12edc0d3ec8190b8b1c8b16884ef64`	completed	May 24, 2026, 12:23 p.m.
NED2	Entity disambiguation (via description)	`batch_6a12ee56948881908c58657e262882a0`	completed	May 24, 2026, 12:25 p.m.

Created at: April 27, 2026, 5:04 p.m.