Triple

T21567745
Position Surface form Disambiguated ID Type / Status
Subject Secretary-General of the Shanghai Cooperation Organisation E532204 entity
Predicate officeHoldersInclude P537 FINISHED
Object Vladimir Norov
Vladimir Norov is an Uzbek diplomat and politician who has served in senior governmental and international roles, including leading the Shanghai Cooperation Organisation.
E2286791 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: Vladimir Norov | Statement: [Secretary-General of the Shanghai Cooperation Organisation, officeHoldersInclude, Vladimir Norov]
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: Vladimir Norov
Triple: [Secretary-General of the Shanghai Cooperation Organisation, officeHoldersInclude, Vladimir Norov]
Generated description
Vladimir Norov is an Uzbek diplomat and politician who has served in senior governmental and international roles, including leading the Shanghai Cooperation Organisation.

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_69e0c460db088190828c64206a450273 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eee9c9f264819085b4807923860793 completed April 27, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a472604b0648190aa53209d199d6f73 completed July 3, 2026, 3:01 a.m.
NEDg Description generation batch_6a472b689e3081909e50582f5c1d913c completed July 3, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_6a472d3fba908190b05706e4d7b83df5 completed July 3, 2026, 3:32 a.m.
Created at: April 16, 2026, 6:30 p.m.