Triple

T193263
Position Surface form Disambiguated ID Type / Status
Subject Anna Eleanor Roosevelt E3764 entity
Predicate givenName P17 FINISHED
Object Eleanor E5505 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: Eleanor | Statement: [Anna Eleanor Roosevelt, givenName, Eleanor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eleanor
Context triple: [Anna Eleanor Roosevelt, givenName, Eleanor]
  • A. Eleanor chosen
    Eleanor is a feminine given name most famously borne by Eleanor Roosevelt, the influential First Lady of the United States and human rights advocate.
  • B. Eleanor
    Eleanor was one of the merchant ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest against British taxation in 1773.
  • C. Margaret
    Margaret is a feminine given name of Greek origin, traditionally associated with the meaning "pearl" and widely used in English-speaking countries.
  • 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. Elizabeth Erving
    Elizabeth Erving was the wife of American statesman and Massachusetts governor James Bowdoin, connecting her to a prominent colonial New England political family.
  • 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_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a2596810c48190ab687c0c2efaa9e2 completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a376589afc8190865a988b5dc71497 completed Feb. 28, 2026, 11:12 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.