Triple

T11456252
Position Surface form Disambiguated ID Type / Status
Subject Simone Moro E271535 entity
Predicate givenName P17 FINISHED
Object Simone E152444 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: Simone | Statement: [Simone Moro, givenName, Simone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simone
Context triple: [Simone Moro, givenName, Simone]
  • A. Simone chosen
    Simone is a feminine given name of Hebrew origin meaning "hearkening" or "one who listens," widely used across various cultures.
  • B. Simone Tata
    Simone Tata is an Indian businesswoman best known for transforming Lakmé into a leading cosmetics brand and playing a key role in the Tata Group’s consumer business expansion.
  • C. Simone Bent
    Simone Bent is an American actress and activist best known as the wife of actor Troy Garity and for her involvement in social and political causes.
  • D. Simone Kahn
    Simone Kahn was a French intellectual and early supporter of the Surrealist movement, known for her close involvement with avant-garde circles in Paris in the 1920s.
  • E. Nadine
    "Nadine" is a classic 1964 rock and roll song by Chuck Berry, known for its vivid storytelling and driving guitar riff.
  • 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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d81c71b1208190be1d5623d18e0222 completed April 9, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d3e197c881909db2e4e59c61c3c3 completed April 20, 2026, 7:21 a.m.
Created at: April 8, 2026, 9:35 p.m.