Triple

T27930334
Position Surface form Disambiguated ID Type / Status
Subject Yongchang Mausoleum E707961 entity
Predicate hasNameInChinese P4878 FINISHED
Object 永昌陵
永昌陵是中国明代皇室成员的陵寝之一,以其历史价值和帝王陵墓建筑格局而著称。
E1795398 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: 永昌陵 | Statement: [Yongchang Mausoleum, hasNameInChinese, 永昌陵]
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: 永昌陵
Triple: [Yongchang Mausoleum, hasNameInChinese, 永昌陵]
Generated description
永昌陵是中国明代皇室成员的陵寝之一,以其历史价值和帝王陵墓建筑格局而著称。

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_69ef96bbf2c48190a9d0e0291457aab6 completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63a64621481908dcf5fb94c528d2b completed May 2, 2026, 5:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13037c35ac8190b8f7b42284ed2429 completed May 24, 2026, 1:56 p.m.
NEDg Description generation batch_6a13076ecce08190a219ae9f8093a9aa completed May 24, 2026, 2:13 p.m.
NED2 Entity disambiguation (via description) batch_6a1308041c648190b5ff53f67dcb142e completed May 24, 2026, 2:15 p.m.
Created at: April 27, 2026, 7:02 p.m.