Triple

T915173
Position Surface form Disambiguated ID Type / Status
Subject Fannie Lou Hamer E19752 entity
Predicate givenName P17 FINISHED
Object Fannie E45356 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: Fannie | Statement: [Fannie Lou Hamer, givenName, Fannie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fannie
Context triple: [Fannie Lou Hamer, givenName, Fannie]
  • A. Fannie chosen
    Fannie is a feminine given name, often used in English-speaking countries and historically associated with figures such as the American cookbook author Fannie Farmer.
  • B. Doris
    Doris is an Oceanid from Greek mythology, known as the wife of the sea god Nereus and mother of the Nereids.
  • C. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • D. Lucille
    Lucille is the famous black Gibson guitar closely associated with blues legend B.B. King, who named all his guitars by this name.
  • E. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • 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_69a4939f91a08190ba68c2c81eab90fe completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2f605bc8190a5245aa2ca55cf43 completed March 1, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf6062e48190ad7efca6da7d0445 completed March 4, 2026, 6:21 a.m.
Created at: March 1, 2026, 7:39 p.m.