Triple

T1475513
Position Surface form Disambiguated ID Type / Status
Subject Clementina E30830 entity
Predicate relatedName P3889 FINISHED
Object Clementine E3423 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: Clementine | Statement: [Clementina, relatedName, Clementine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clementine
Context triple: [Clementina, relatedName, Clementine]
  • A. Clementine chosen
    Clementine is a feminine given name most famously borne by Clementine Churchill, the wife of British Prime Minister Winston Churchill.
  • B. Berry
    Berry is a historic province in central France known for its rural landscapes, medieval heritage, and traditional French culture.
  • C. Clémentine
    Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
  • D. Mikan
    Mikan is a surname most famously associated with George Mikan, a pioneering American professional basketball player often regarded as the NBA’s first dominant big man.
  • E. Malus
    Malus is a genus of deciduous trees and shrubs in the rose family best known for cultivated apples and ornamental crabapples.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c602387c8190b97a20c8e05e3d16 completed March 1, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1ca21f288190b5f6f9a5895cdcf0 completed March 8, 2026, 6:52 a.m.
Created at: March 1, 2026, 8:11 p.m.