Triple

T30185146
Position Surface form Disambiguated ID Type / Status
Subject Samira E767316 entity
Predicate hasVariant P455 FINISHED
Object Samirah
Samirah is a feminine given name, often of Arabic origin, associated with meanings like "companion in evening talk" or "entertaining companion."
E1904950 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: Samirah | Statement: [Samira, hasVariant, Samirah]
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: Samirah
Triple: [Samira, hasVariant, Samirah]
Generated description
Samirah is a feminine given name, often of Arabic origin, associated with meanings like "companion in evening talk" or "entertaining companion."

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_69f2247cc3d88190811dec3face94bf5 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67f44a24c8190bbc5bdbc0ef3bcca completed May 2, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2764359bdc81908785aac9c79d2a4e completed June 9, 2026, 12:54 a.m.
NEDg Description generation batch_6a2764dcc7148190b7ba48ce073f845f completed June 9, 2026, 12:57 a.m.
NED2 Entity disambiguation (via description) batch_6a2765db45d88190817f04133b5efd75 completed June 9, 2026, 1:01 a.m.
Created at: April 29, 2026, 7:27 p.m.