Triple

T11713167
Position Surface form Disambiguated ID Type / Status
Subject Josephine Baker E278422 entity
Predicate alsoKnownAs P39 FINISHED
Object La Baker E278422 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: La Baker | Statement: [Josephine Baker, alsoKnownAs, La Baker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Baker
Context triple: [Josephine Baker, alsoKnownAs, La Baker]
  • A. La Baker chosen
    La Baker is the nickname of Josephine Baker, the iconic American-born French entertainer, civil rights activist, and World War II resistance agent.
  • B. Baker
    Baker is a common English occupational surname originally given to people who baked bread or worked in a bakery.
  • C. Baker
    Baker is a small desert town in San Bernardino County, California, known as a roadside stop and gateway to Death Valley for travelers along Interstate 15 between Los Angeles and Las Vegas.
  • D. Baker
    Baker is a residential dormitory at the Massachusetts Institute of Technology known for its distinctive architecture and vibrant student community.
  • E. Baker
    Baker was the second of the 1946 Operation Crossroads nuclear tests at Bikini Atoll, notable as an underwater detonation used to study the effects of nuclear explosions on naval ships and equipment.
  • 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_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4be10088190854699385d1f6a95 completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef838562d08190b9a764e88c50d423 completed April 27, 2026, 3:40 p.m.
Created at: April 8, 2026, 9:40 p.m.