Triple

T37542512
Position Surface form Disambiguated ID Type / Status
Subject Embassy of China in Iran E933365 entity
Predicate associatedWith P37 FINISHED
Object China–Iran relations
China–Iran relations encompass the diplomatic, economic, and strategic ties between the People’s Republic of China and the Islamic Republic of Iran, including cooperation in energy, infrastructure, and regional security.
E2232009 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: China–Iran relations | Statement: [Embassy of China in Iran, associatedWith, China–Iran relations]
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: China–Iran relations
Triple: [Embassy of China in Iran, associatedWith, China–Iran relations]
Generated description
China–Iran relations encompass the diplomatic, economic, and strategic ties between the People’s Republic of China and the Islamic Republic of Iran, including cooperation in energy, infrastructure, and regional security.

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_69f76ec999288190ae26ec7b6aea7046 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba420dac48190848c26e3b360a750 completed May 6, 2026, 8:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a409f081d608190a8dd3e3b8393c8a9 completed June 28, 2026, 4:11 a.m.
NEDg Description generation batch_6a409f9eb63c8190866e647770e86bb3 completed June 28, 2026, 4:14 a.m.
NED2 Entity disambiguation (via description) batch_6a40a0aa945c81909a9b8ab5b797d45a completed June 28, 2026, 4:18 a.m.
Created at: May 3, 2026, 4:17 p.m.