Triple

T1586978
Position Surface form Disambiguated ID Type / Status
Subject Amelia Boynton Robinson E34087 entity
Predicate givenName P17 FINISHED
Object Amelia E134547 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: Amelia | Statement: [Amelia Boynton Robinson, givenName, Amelia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amelia
Context triple: [Amelia Boynton Robinson, givenName, Amelia]
  • A. Amelia chosen
    Amelia was a British princess of the early 18th century, the daughter of King George II and Queen Caroline of Ansbach.
  • B. Betsy
    Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
  • C. Henrietta
    Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
  • D. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • E. Alix
    Alix is the given name of Alix of Hesse and by Rhine, who became Empress Alexandra Feodorovna of Russia as the wife of Tsar Nicholas II.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9090b3a20819098fdb5605ee739d7 completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad469b36548190b2bdf2324fbea30f completed March 8, 2026, 9:51 a.m.
Created at: March 4, 2026, 7:27 p.m.