Triple

T28075985

Position	Surface form	Disambiguated ID	Type / Status
Subject	Huang Yueying	`E709542`	entity
Predicate	father	`P120`	FINISHED
Object	Huang Chengyan Huang Chengyan was a reclusive, eccentric scholar of the late Eastern Han period, best known in history and Romance of the Three Kingdoms as the father of Zhuge Liang’s talented wife, Huang Yueying.	`E1802517`	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: Huang Chengyan | Statement: [Huang Yueying, father, Huang Chengyan]

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: Huang Chengyan
Triple: [Huang Yueying, father, Huang Chengyan]

Generated description

Huang Chengyan was a reclusive, eccentric scholar of the late Eastern Han period, best known in history and Romance of the Three Kingdoms as the father of Zhuge Liang’s talented wife, Huang Yueying.

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_69ef9b6f8078819098b741274cd1a2ee`	completed	April 27, 2026, 5:22 p.m.
NER	Named-entity recognition	`batch_69f6403feb908190a919f46b3c5a3abd`	completed	May 2, 2026, 6:19 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a15c912867c8190aa37a74e16988b61`	completed	May 26, 2026, 4:23 p.m.
NEDg	Description generation	`batch_6a15ca1e992c819099d74611836ba016`	completed	May 26, 2026, 4:28 p.m.
NED2	Entity disambiguation (via description)	`batch_6a15cbdf46208190916381816f411f87`	completed	May 26, 2026, 4:35 p.m.

Created at: April 27, 2026, 8:49 p.m.