Triple

T26902322
Position Surface form Disambiguated ID Type / Status
Subject 建邺区 E678064 entity
Predicate hasLandmark P105 FINISHED
Object 江苏大剧院
江苏大剧院是位于南京市建邺区的一座大型现代化综合剧院与文化艺术地标。
 E1748646 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: 江苏大剧院 | Statement: [建邺区, hasLandmark, 江苏大剧院]
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: 江苏大剧院
Triple: [建邺区, hasLandmark, 江苏大剧院]
Generated description
江苏大剧院是位于南京市建邺区的一座大型现代化综合剧院与文化艺术地标。

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_69eee9befee48190a26f214faa867be7 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61fb05f8c819098c801df80e58551 completed May 2, 2026, 4 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121eaa66688190afb61b4865d8a86d completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a121fcbbfa88190920877882c038ac8 completed May 23, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a1220621c4c81909da5a95967d52202 completed May 23, 2026, 9:47 p.m.
Created at: April 27, 2026, 5:51 a.m.