Triple

T8476254
Position Surface form Disambiguated ID Type / Status
Subject Lara Logan E200400 entity
Predicate name P16 FINISHED
Object Lara Logan E200400 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: Lara Logan | Statement: [Lara Logan, name, Lara Logan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lara Logan
Context triple: [Lara Logan, name, Lara Logan]
  • A. Lara Logan chosen
    Lara Logan is a South African television and radio journalist best known for her high-profile foreign correspondence and war reporting for CBS News.
  • B. Andrea Mitchell
    Andrea Mitchell is an American television journalist and longtime NBC News correspondent known for her coverage of U.S. politics and foreign affairs.
  • C. Christiane Amanpour
    Christiane Amanpour is a prominent British-Iranian journalist and television host best known as CNN’s chief international anchor and for her in-depth coverage of global conflicts and politics.
  • D. Judy Woodruff
    Judy Woodruff is an American broadcast journalist best known for her long tenure as a leading anchor and managing editor of PBS’s flagship news program.
  • E. Maria Bartiromo
    Maria Bartiromo is an American financial journalist and television news anchor known for her pioneering work on CNBC and later Fox Business Network.
  • 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_69ca831b17988190a1f3f3413d57b820 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe51e21548190811e3c7ba7b196e5 completed March 31, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce3a0f5e088190b70b2c7437884b3b completed April 2, 2026, 9:42 a.m.
Created at: March 30, 2026, 6:12 p.m.