Triple

T23947513
Position Surface form Disambiguated ID Type / Status
Subject FC Anzhi Makhachkala E602953 entity
Predicate signedPlayer P27784 FINISHED
Object Lassana Diarra
Lassana Diarra is a French former professional footballer, primarily a defensive midfielder, who played for top European clubs including Chelsea, Arsenal, Real Madrid, and Paris Saint-Germain, and represented France at international level.
E1609755 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: Lassana Diarra | Statement: [FC Anzhi Makhachkala, signedPlayer, Lassana Diarra]
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: Lassana Diarra
Triple: [FC Anzhi Makhachkala, signedPlayer, Lassana Diarra]
Generated description
Lassana Diarra is a French former professional footballer, primarily a defensive midfielder, who played for top European clubs including Chelsea, Arsenal, Real Madrid, and Paris Saint-Germain, and represented France at international level.

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_69e2953e4924819093f1c24c03476b42 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d02fb4fc8190835baf3bcf909d4d completed April 29, 2026, 9:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f765369908190b92e22095f9a3032 completed May 21, 2026, 9:17 p.m.
NEDg Description generation batch_6a0f770a063c81909f356346c9c521ad completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f782b47c08190a221c196ddc9d566 completed May 21, 2026, 9:24 p.m.
Created at: April 17, 2026, 9:18 p.m.