Triple

T602451
Position Surface form Disambiguated ID Type / Status
Subject Catharine Beecher E11522 entity
Predicate givenName P17 FINISHED
Object Catharine E8723 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: Catharine | Statement: [Catharine Beecher, givenName, Catharine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catharine
Context triple: [Catharine Beecher, givenName, Catharine]
  • A. Catherine chosen
    Catherine is a feminine given name of Greek origin, derived from Aikaterine and widely used in various forms across many cultures.
  • B. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • C. Abigail
    Abigail is a feminine given name of Hebrew origin meaning "my father is joy," historically popular in English-speaking countries.
  • D. Agnes of Sorrento
    Agnes of Sorrento is a historical novel by Harriet Beecher Stowe set in Renaissance Italy, exploring themes of faith, love, and moral conflict.
  • E. Margaret
    Margaret is a feminine given name of Greek origin, traditionally associated with the meaning "pearl" and widely used in English-speaking countries.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d7c08648190bbffc8adb4148987 completed March 1, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a56930dfd88190a991adafc406c5ac completed March 2, 2026, 10:40 a.m.
Created at: March 1, 2026, 7:35 p.m.