Triple

T27072108
Position Surface form Disambiguated ID Type / Status
Subject World Blitz Chess Championship 2013 E685354 entity
Predicate hasParticipant P149 FINISHED
Object Shakhriyar Mamedyarov
Shakhriyar Mamedyarov is an Azerbaijani chess grandmaster known for his aggressive playing style and status as one of the world's top players.
E1766138 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: Shakhriyar Mamedyarov | Statement: [World Blitz Chess Championship 2013, hasParticipant, Shakhriyar Mamedyarov]
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: Shakhriyar Mamedyarov
Triple: [World Blitz Chess Championship 2013, hasParticipant, Shakhriyar Mamedyarov]
Generated description
Shakhriyar Mamedyarov is an Azerbaijani chess grandmaster known for his aggressive playing style and status as one of the world's top players.

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_69ef14843b1481909d828b3d5a44550a completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f6231257f481909d576c19559e0ad0 completed May 2, 2026, 4:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129c8ae08c8190a6b93a6905443d84 completed May 24, 2026, 6:36 a.m.
NEDg Description generation batch_6a129d8d0cec8190866152cb9edfefe7 completed May 24, 2026, 6:41 a.m.
NED2 Entity disambiguation (via description) batch_6a129e0f2dc081909e404f6c9fcd3b0b completed May 24, 2026, 6:43 a.m.
Created at: April 27, 2026, 8:28 a.m.